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The 145-pound division was practically made for Cyborg, and Nunes dominated her. That is everything there is to it.
I vividly recall Baszler’s leg kick TKO loss as a big fan of leg kick TKOs. I had no idea, however, that Amanda was the one who had done it. It’s crazy to think I was watching the future women’s GOAT at the time and had no idea who she was.
Except for Valentina, who will always be at a disadvantage due to her height, she has no competition. And, as we saw on this weekend’s card, when you have two highly qualified fighters, size does matter.
If they run it back, I still believe Cyborg can get her.
Since she beat Nunes in the standup department, Germain should be able to develop her ground game even further.
Nunes might be nice, in my opinion.
There is no middle ground in all of the fights; they either end early or go all the way to the final round.
All you have to do now is keep lining them up. No one is deserving, worthy, or capable of challenging her, so Amanda can continue to set records.
She should simply begin battling the top bantamweight and featherweight contenders simultaneously.
Nonetheless. A barn is impossible to sell.
I believe she has defeated more than half of the female fighters who have won a UFC championship. It’s insane.
Edit: She has defeated 6 of the 12 champions, but naming Nicco Montao a former champion isn’t fair, so I’ll stick with saying she has beaten more than half of them.
Valentina is the only one who has come close to defeating her, and she has done so twice. I have no idea how long it will be before she loses or meets another serious opponent.
WMMA Goat, without a doubt—but I’m hoping they will find better challengers than Spencer and Anderson here. Oh, no.
I’ve never seen a fighter look when defeated as Anderson did as he entered the ring.
If Max vs Volk 3 takes place, Valentina vs Nunes 3 must take place as well.
Anyone other than the GDR and Shevchenko has no chance.
And though she’s 2-0 against both, she should fight them again.
Ngannou is what she needs.
The war to make is Cat Zingano.
Watch as a new fighter makes his ufc debut and wins a first-round tko in the 135 division’s next title contest.
Nunes’ latest win streak is now longer than Ronda’s entire MMA career, according to a statistic I saw over the weekend.
Given that the win streak is almost entirely made up of championship fights, it’s very impressive.
The number of posts I saw claiming Megan has it all together and would make people money was hilarious. Betting odds gives a false sense of optimism.
I’m able to discuss the G.O.A.T. and everyone else who might be superior to herher some better challengers than Spencer and Anderson. Oh, no.
If only she could box like Ronda.
She’s a level 100 character who’s always on Easy mode.
And Shevchenko was the only one who caused her any trouble; none of the other fights were even close to being competitive. It’s a little crazy. Like her previous decision with Spencer, it seemed as though she just wanted to harass the girl for five rounds.… and look at how many of the women’s elite of all time are on the same streak.
The only living legend she hasn’t faced is Roxanne Modafferi… and we all know how that ends for Roxy.
Now I have to learn how nunes will beat men once more.
Val is the only woman who has ever come close to succeeding against her. There are a few names that may be considered the men’s GOAT, but Nunes is without a doubt the women’s GOAT.
Valentina is someone she wants to fight again.
She is the only woman who has dared to question her.
She was forced to a three-round decision in her first match.
Second place was lost due to an SPLIT vote.
Since then, she’s been in charge of her own division.
It’s the only thing that makes sense if we want to see Amanda actually fight.
The Amanda Nunes Hall of Fame will be named after Ronda Rousey, who will have her own wing in the hall of fame.
The chances of all of her rivals getting exactly four defeats are astronomical.


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I have a 600 MHz ZTE Score, ARM v6, Android 2.3.4, and an Adreno 200 GPU @ 466 MHz (requiring software rendering; no OpenGL ES 3.0 support). I was wondering if I can possibly boot at least a single game for one of the older versions of Dolphin. I tried very early releases, but the apps do not launch and GUI doesn't show (they all crash super fast).
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20+ years ago I started work at a thriving Natural Health Centre, practising the energy therapy kinesiology; the art of using muscle testing to identify imbalances in the body’s energy system.
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Often when I asked my clients when their symptoms first started, it usually coincided with a significant event in their life, or a choice that they made, but they’d never realised the connection before.
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One client would insist on working all hours, even though she was exhausted, saying that ‘she didn’t have time to stop.’ And every time she ignored the cries from her body, she would end up in bed for over a week with sciatica, and no choice, but to rest!
As time went on, these clients, now symptom free, would then come back for routine tune-ups to ensure that everything was running smoothly and to nip issues in the bud to make sure that symptoms didn’t return.
Today, I often hear that women are doing the internal work, but still feel as if they’re going around in circles, that they’ve lost their drive, lack passion and purpose, all of which causes them to feel down and often powerless.
Basically, they feel disconnected.
When these patterns are re-balanced my clients re-discover who they are at the core of their being – their fully expressed Divine SHEro Goddess, Wild Woman self.
Not only do the symptoms seemingly disappear, but the ripple effects of this work permeates throughout all areas of your life, creating space for powerful shifts in a way that feels fully supported and safe.
What happens in our inner lives shapes our outer realities
Since 2000 I have been working with clients, using the energy therapy Kinesiology, to help them find clarity, remove blocks, become unstuck.
I love supporting my clients by helping them to release what no longer serves them. When you can let go of the patterns that have been holding you back, you are then ready to move forward with your life.
I have a new found confidence which continues to grow and have more meaning in my life. My life had moved on in two months working with Rebecca than it had in the previous 2 years.”  Susan Leadbeater, Staffordshire, UK
I truly have deep admiration and soul appreciation for Rebecca, and honour her work as deeply significant for the progress of our worldwide sisterhood.”  Lysa Black, New Zealand
“Rebecca is a genuine ally to have on your life’s journey.
That gift helped me change my life.
She provided great insights that helped me to clear up energetic and emotional blockages I have had for years. It was as if my mind, body and soul were finally in alignment. Since then I have had two other sessions with her and my life has found a flow that I have never known possible as I have moved on to start two businesses, develop a positive relationship with money, build up my relationships and use my true voice in the world with confidence.”  Angelique Duncan
She is able to facilitate their release in a quick and effective manner that will leave you feeling clearer and lighter.  Her insight during this process is invaluable and spot on.  She is powerful and straight to the point while holding compassionate and joyful sacred space for you.  I always call her when I’m dealing with stubborn blocks I can’t shift on my own and I love that with her we can just get in and get it done and I can get back to my magical self.”  Ruby Toad, Canada
Stop hiding and pretending: It’s time to find your purpose in life
My Story, On Purpose
Growing up in a sleepy fishing village on the south coast of Cornwall, I found myself reading ‘Teach Yourself Yoga’ books, whilst my friends around me were reading the latest teen magazines.
I’ve no idea what drew me to yoga, but something woke inside of me, and I found myself on a quest.
I didn’t have the language for this quest I embarked on, but it ignited within an insatiable desire for knowledge.
I found myself seeking.
Asking questions about life, and my purpose in life.
I’d heard the term ‘soul purpose’, and it resonated within me.
I wanted to know my soul purpose.
I created this idea that once I knew what my soul purpose was, everything in my life would make sense, and everything would fall into place.
I didn’t know what that ‘place’ was, or looked like, but I knew I’d arrive there once I knew my soul purpose.
I searched for books (these were the days before Amazon!).
I read the books.
Took more personality profiles than I can remember.
And still I kept searching for more.
I was searching for meaning, and that meaning for me looked like a quest to find my soul purpose – whatever that actually was…
For years, well more like decades, I read, attended courses, had healings, trained in modalities.
And carried on seeking for my elusive soul purpose.
What was I here to do and contribute?
Each time I learnt something new, uncovered a bit more about my personality profile, astrological chart, Human Design… I thought ‘Yes, this is it! This is who I am and what I’m meant to do.’
What felt great initially, started to wear off.
It wasn’t quite right.
Something was ‘missing’, so off I’d go again in search of the next thing, in search of that one  ‘missing’ part.
Now of course, all of these things were valuable to me.
Fascinating in their own right.
And each piece useful in learning more about myself.
But it wasn’t filling the hole I was trying to fill with my seeking.
Then one day, BOOM!
I’m not sure what or why, but I had the realisation that my seeking wasn’t me following the ‘spiritual’ path.
It wasn’t me being virtuous on a quest to know myself fully.
It was me avoiding living my life fully.
I’d been seeking for my soul purpose as if it was a job title.
But in fact, what I’d been searching for was permission to be me.
Each book I’d read, training I’d attended, or reading that I’d had done, I wanted it to confirm what I wanted. I wanted it to validate who I was, I wanted to know I was ‘right’ in my interests, dreams, and desires.
I’d been looking for external validation of who I was and what I wanted to do, as I’d been too afraid to give that same permission to myself.
If it was ‘written in the stars’, well it couldn’t be my ‘fault’, it was just destined to be that way.
If it was in my birth chart, my personality profile, or Human Design, how could I be ‘blamed’ for following a particular path?
When we grow up, we often find ourselves trying to fit in.
We subconsciously find ourselves asking ‘Who do I need to be to fit in or to be loved’ within this family/situation/group of people?’
And because I wasn’t directly asking other people, I didn’t realise I’d still fallen into this pattern.
I wasn’t asking people, but I was still looking outside of myself.
A couple of times people would say to me ‘all the answers are within’, and I’d roll my eyes, smile politely, and go seeking elsewhere.
Annoyingly, it was true.
All of those years of seeking, and the answers had been within.
Deep down, I did know who I was and what my life purpose was, but it had been buried under more than enough life events to keep it from being seen clearly by me.
Then that one day, I realised that I’d been hiding the truth from myself.
I’d been pretending I didn’t know the answers to the questions I’d been seeking.
Because if I did know.
Because if I stopped pretending.
Then I’d have to make changes.
I’d have to do what I knew to be true and stop doing what other people expected of me.
I’d have to disappoint other people and prioritise myself.
I’d have to let other people down, so I could focus on me.
I’d have to say ‘No’ to others, so I could say ‘Yes’ to me.
Now being British I’m all too familiar with ‘Being too big for your boots’, and the feeling of ‘Who does she think she is to put herself first?’.
Unfortunately, it’s not unique to us here in the UK.
In Australia they have ‘tall poppy syndrome, and in the USA I believe the term is ‘being too big for your britches’. And no doubt there are similar phrases all over the world.
The result being that when you realise that you do know what you want or need to do, it is way easier to pretend that you don’t.
At least on the surface, and in the short-term, it feels easier.
But actually, to betray yourself, your needs, and desires, is in fact the harder option in the end…
You have to give yourself permission to disappoint others, to let them down, to say no to their ideas and dreams for you, so that you can:
Say ‘Yes’ to your own dreams and desires.
Say ‘Yes’ to knowing who you are and what you want from life.
Say ‘Yes’ to loving yourself first.
Say ‘Yes’ to living a life that you love.
Because when you don’t, when you hide, and pretend that you don’t know who you are and what you want from life, that leads to disappointment, disloyalty, heartache, anger and resentment from yourself, directed towards yourself.
You learn not to trust yourself.
You dismiss your feelings, insights, and dreams.
You become a shell of who you are here to be.
And that’s no fun for anyone!
PS. You might wonder what my big realisation was….
I simply realised that my soul purpose in life, was the same as yours, the same as I believe everyone’s is…
And that’s to be more of ourselves.
I’d spent all those years looking for someone else to tell me who I was, what my purpose in life was. When all the time it had simply been looking for permission to be more of myself.
I’d been seeking permission to be me.
No finished article, no job title, no destination. Just the beautifully messy, perfectly imperfect, unfolding, unravelling, unfurling process of being more me.
I’m aware that I could sound crazy… But… I saw a dragon
It all started last week when a yellow dragon was circling my room.
Yes, I know that sounds crazy, and no it wasn’t ‘real’ like a cat wandering into my room, but it was ‘real’ in that I could see it and sense it…
I was in the middle of an energy activation for the year ahead for my Re-Enchant community. The session itself focused on activating confidence and releasing the need for validation from others.
And interestingly TRUST was becoming a clear theme in the session.
As I was working through the session, I suddenly became aware of a huge golden-yellow dragon circling in my office.
I often sense energies whilst doing energy work, but this dragon was clearly trying to get my attention.
At first I ignored it.
But it was clear that it wasn’t about to leave any time soon
I didn’t initially share what I could see with the group – as yes, I’m aware at how weird it sounds, but it was so insistent that I had to share.
I also wanted to share what I could see with the group,  as I knew it wasn’t my dragon (more on that in a minute lol).
So I asked the group if any of them worked with dragons and a few of them did. Then I asked if anyone worked with a golden-yellow dragon and I got a very strong ‘yes’ from one of the members (maybe the response actually included words not suitable for children lol), as she had indeed been ignoring this dragon. Among other things she told me that this dragon reminded people to trust their intuition – one of the themes from the session!
Anyway the golden-yellow dragon eventually left.
I really don’t want my office to be home to the energies and allies that people are ignoring lol!
But the archetypal dragon energy didn’t leave.
Back in 2018 I had a very strange experience with dragons – but that’s a whole other story that included a visit to hospital, emergency surgery and ‘giving birth’ to a ‘dragons egg’ (which the Dr. named Pete!)… Does that make me a Dragon Mother? 😉
Anyway… my dragons aren’t the flying dragons I experienced during the energy session last week, the dragon energy I’ve encountered in the past has been much more earth-based. More like giant serpents undulating through the ground.
Showing my age… I described them as looking more like the creatures in the film Tremors, to which my friend responded she had imagined them to be like from the film Dune. and when I did a quick google ‘Yes’ to Dune creatures (a film that I hadn’t seen), and ‘No!’ to Tremors – those creatures were waaaay more gruesome than I remember haha
Anyway… after the experience with the golden-yellow dragons, my own dragons are back and wanting me to work more with the land energies.
The call to walk the land and connect with nature, and in particular the trees, was so strong that I asked the members of the Re-Enchant Community if they want to join me in some land connection work too, which involves working with the eight Sabbat/Earth Festivals, and includes:
Creating our own Ogham
Creating Sacred Tree healing discs
All from an energy clearing session that woke my dragons haha
As I said at the beginning, I know sharing this makes me sound a little ‘out-there’. I often joke that if my sister, who’s a mental health nurse, sat in on one of my sessions she may well be concerned for me…
But this is my reality. Of course I don’t see dragons all the time, but I do believe we can be much more aware of things than we can typically see with our senses, and that we’re taught are ‘real’.
I’d love to hear if you have any experiences of things that make you sound ‘out there’.
I look forward to hearing your experiences!
As soon as I heard the term ‘Sacred Pause’, my body recognised it and sighed ‘yes’.
The Sacred Pause is a term I learnt from Molly Remer, who learnt it from Joanna Powell Colbert and is a central theme in my work.
I loved that there was a phrase that matched the energy I knew was needed and essential to everyone of us.
In a world that values doing and achieving, giving yourself time to be and brew, to honour the need of the Sacred Pause can be hard.
Yet the Sacred Pause is at the heart of life.
When you breathe, you breathe in, pause, and then breathe out. Without this pause you’d likely faint!
I like to think of it along the lines of walking the labyrinth.
When you walk a labyrinth, you enter with intention, often to seek the answer to a question you hold in your heart.
As you spiral in, you let go and release all of the things that are preventing you from finding the answer you seek.
Then when you get to the centre you pause.
The Sacred Pause where you allow yourself to assimilate. To allow the answer a chance to come to you. This is where the transformation and inspiration occurs.
Then when you’re ready, you spiral back out of the labyrinth, transformed, a new person, never to be the same again.
The Sacred Pause being quite literally the heart and the centre of this transformation and experience.
And then you really *KNOW*
I often think you know things and then you really *know* things.
I had this experience about the Sacred Pause – although I didn’t have a name for it then, when I started doing Kundalini Yoga.
I’d been dabbling with Yoga for years, and for me it had always had a focus on fitness and flexibility.
I was surprised when I started Kundalini Yoga, as we’d hold a pose, and then rest for longer than we’d held the pose.
Initially I noticed I was frustrated by this. I wanted to stretch and feel like I was ‘doing’ something.
And immediately noticed that in the Pause, in the rest, I could feel my energy releasing and moving around my body.
I started to value the importance of the rest, rather than the doing.
I realised that in the rest we were making the space for the magic to happen.
Ever since then I have honoured the Pause as much as the doing, understanding that both are needed.
I definitely have a tendency to be prone to more doing, but I always ensure that each day I take moment to pause and check in with myself.
To Pause and allow the integration to happen.
To Pause and allow life to come to me.
If you’d like some help to embrace and experience the magic of the Sacred Pause I have a free practice for you, simply CLICK HERE
Inspired by a jumpsuit…
Here’s something you probably don’t know about me… It’s not very important, but it did make me think about change today… And that’s…
I’ve never known what colour or style suits me.
I go snow blind as soon as I walk into a clothes shop.
I’m not sure where this has come from, but I’ve never enjoyed it.
Shopping is too hard….
My bum has always been ‘too big’ compared with my waist, so finding trousers that don’t ridiculously gape at the back is a nuisance, my legs seem to be in between lengths lol… I could go on… but I’m sure you get the picture…
I think I missed the part of being a teenager where you learn how to dress and find what suits you.
And now of course I’m on the other side of 40, still wondering what clothes I should buy!
So I choose another way
Last month I booked a consult with a stylist who tells you what colours you look best in and what styles work for you.
It was such fun! If you haven’t done it before, I highly recommend it!
And if you know colours and are curious… I’m ‘Summer’ and need to wear cool colours, like blues, dark green and burgundy.
But knowing what to wear and buying it are two completely different things!
So I booked  a session with the same inspiring woman to go personal shopping, and oh my… what a totally different experience!
She loved shopping and knew exactly what to look for that would suit me.
She picked things for me that I wouldn’t have even looked at
I kept shaking my head… and am still shaking my head chuckling, as I now have
All of which I would never have bought without her help.
And all of which I actually now love! In fact I’m writing to you in one of my jumpsuits! (yes I have more than one now!!)
And it go me thinking…
The jumpsuit got me thinking about change.
As humans we’re not really good at change…
Whether it’s a change to how we see ourselves, change in the type of clothes we wear, or the relationships we have.
We can resist it, ignore it, fight it …
I know that I’ve even resisted change that I knew would be beneficial to me in the long run!
I could despair at myself lol, but instead I look to nature…
Nature has so much to teach us about change. About starting over, again, and again and again.
As humans we’re taught that time is linear.
There’s a start, and a series of steps that moves you towards an end goal.
Each of those steps builds on the previous step, and you’re expected to become bigger, stronger, and more successful with each of those steps.
But in this model, there’s no space for failure, for stumbling a few steps back, for starting over. No place for rest or a reset.
But when we remember that we are intimately connected to nature, and we can model our experience on hers, we realise that life is in fact a spiral path and not a linear path.
On a spiral path we can allow ourselves to start again.
We can give ourselves permission to rest and pause. To change our minds, to reset, to revisit, to regroup and start over.
On a spiral path there’s no comparison, so no place for fear, blame or shame.
When we remember that we are intimately connected to nature we can embrace the spiral path and give ourselves permission to start over, to start again and change.
With love, jumpsuits and spirals


Downside School founded 1606adstock, Somerset , United Kingdom. Downsid20i6th to 12th . Downside School has been educating students for 413years.


I had to drive a Swift car before one month. Last month I had scrapped my car for cash to the "ScrapCarComparison.co.uk". And I want to buy a new car in the next six months and for that my dream car is Mercedes benz.
by maah 9 years ago
by bizijebator 6 years ago.
But I changed it to 2011 Ford Capri as they are going to bring it back. Check the Detroit Auto show 2011 in


Data Science Agile Project Management Machine Learning AI
Learn Data Science Project Structure and Flow For Startups
By Kimberly Cook | Jan 8, 2019 | 2976 Views
I was recently asked by a startup I'm consulting (BigPanda) to give my opinion about the structure and flow of data science projects, which made me think about what makes them unique. Both managers and the different teams in a startup might find the differences between a data science project and a software development one unintuitive and confusing. If not stated and accounted for explicitly, these fundamental diffe
 challenging to incorporate new types of inputs, such as product and business needs, tighter infrastructure and compute constraints and customer feedback, into their research and development process.
The flow was built with small startups in mind, where a small team of data scientists (usually one to four) runs short and mid-sized projects led by a single person at a time. Bigger teams or those in machine-learning-first, deep-tech startups might still find this a useful structure, but processes there are longer and structured differently in many cases.
Figure 1: Data Science Project Flow for Startups
ce, and data engineering.this case, the data scientist is usually in charge of working with developers to help him with these aspects (or does them himself, if he happens to be the rarest of all of God's beasts: the Full Stack Data Scientist! You can thus replace data engineer with data scientist whenever it is mentioned, depending on your environment.
On the time axis, I broke the process down into four distinct phases:
(Model) Development
I'll try and walk you through each of these, in order.
Defining the scope of a data science project is crucial more than in any other type of project.
A project should always start with a product need (even if the original idea was technical or theoretical), a need validated to some degree by product/business/customer success people. The product person should have an idea of how this feature should (roughly) end up looking, and that either existing or new customers will be willing to pay for it (or that it will prevent churn/drive subscriptions / drive sales of other products / etc.).
A product need is not a full project definition, but should rather be stated as a problem or challenge; e.g. "our customers need a way to understand how they spend their budgets" or "we do not manage to get our older users to keep taking their medicine; this increases churn" or "customers will pay more for a product that can also predict rush hours at the airports they run".
1.2. Initial solution ideation
This is where the data scientist, together with the product person in charge, the data engineer and any other stakeholder, come up with different rough sketches for possible solutions. This means both the general approach (e.g. unsupervised clustering vs boosted-tree-based classification vs probabilistic inference) and the data to be used (e.g. this specific table from our database, or some specific user behavior that we do not yet monitor or save, or an external data source).
This usually also involves some level of data exploration. You can't go real deep here, but any promising "low-hanging fruits" can help guide ideation.
The data scientist should lead this process and is usually in charge of providing most of the solution ideas, but I would urge you to use all those taking part in the process for solution ideation; I have had the good fortune to get the best solution ideas for a project handed to me by a back-end developer, the CTO or the product person in charge. Don't assume that different, and less theory-oriented backgrounds, invalidate people from taking part in this phase; the additional minds and viewpoints are always valuable.
1.3. Data preparation and accessibility
The team should now have a good idea of the data that would hopefully be used to explore possible solutions (or at least the first such data set or source). Thus, the process of providing data access and preparing it for exploration and use should already start, in parallel with the next phases.
This can sometimes entail dumping large data sets from production databases into their staging/exploration counterparts, or to colder storage (for example, object storage) if its time availability is not critical in the research phase. Conversely, it can mean pulling large data dumps from very cold storage back into table or document form to enable fast querying and complex computations. Whatever the case, this phase is required for the research phase to start and frequently ends up taking more time than expected, and so that's the right time to initiate it.
1.4. Scope & KPIs
This phase is about deciding together on the scope and the KPIs of the project.
KPIs should be defined first in product terms, but in much more detail than before; e.g. with respect to the three aforementioned product needs, they might become "customers could now use a dashboard with CTR stats and projection per category", or "missed medicine days by users over 65 will be reduced by at least 10% over the next two quarters", or "customers will receive weekly predictions of rush hours in their airports with granularity of at least an hour, and approximation of at least Â±50%".
These KPIs should be then translated into measurable model metrics. With luck, these will be very hard metrics, such as "predicting the expected CTR of an ad with approximation of at least X% in at least Y% of the cases, for an ad that runs for at least a week, and for any client with more than two months of historical data". In some cases, however, softer metrics will have to be used, such as "time required for topic exploration using the generated expanded queries will be shortened, and/or result in quality will improve, when compared to the original queries". This is especially true when the model is meant to assist some complex human function.
Technically even these metrics can be defined very strictly (and in academic research, they usually are), but depending on resources and time constraints we might settle with approximating them using human feedback. In this case, each feedback iteration might take longer, and so we will usually try to find additional hard metrics to guide us through most of the upcoming research iterations, with the costlier feedback being elicited only once every few iterations, or on significant changes.
Finally, scope is especially important here because research projects have a tendency to drag on and to naturally expand in size and scope as new possibilities arise while researching or when an examined approach answers the demands only partially.
Scope limitation 1: I find it more productive to limit scope explicitly; for example, if you've decided that a Multi-Armed Bandit based model is the most promising approach to start with, you might define the project scope to a single two/three weeks iteration of model development, deploying the model regardless of its accuracy (as long as it's over 60%, for example). Then, if improvement in accuracy is valuable (in some cases it might turn out to be less so), developing a second model might be thought of as a separate project.
Scope limitation 2: Another variation on scope limitation is using increasing degrees of complexity; for example, the first project might aim to deploy a model that only needs to provide a rather large set of candidates of ad wording and color variations for your own customer success people to work with; the second might attempt to build a model that gives a smaller set of suggestions that the customer can see himself; and a final project might try for a model that highlights a single option, ranking below it a couple more, and adding CTR projections and demographic reach for each variation.
This is already a huge departure from software engineering, where usually components are iterated over for increased scale rather than complexity.
Nevertheless, the metric-to-product-value function might be a step function, meaning that any model performing under some X value has no use for the customer; in these cases, we will prefer iterating until that threshold is suppressed. However, while this X might be very high in some cases, I believe that both product/business people and data scientists tend to overestimate the height of this step; it's very easy to state that anything under 95% accuracy (for example) provides no value and can't be sold. In many cases, however, careful examination and challenging of product assumptions can lead to very valuable products that might not be as demanding technically (at least for the first iteration of the product).
1.5. Scope & KPIs approval
Finally, the product person in charge needs to approve the scope and KPIs defined. It is the data scientist's job to make sure everybody understand the implications of the scope - what was included and what was prioritized - and the relation between the product KPIs and the harder metrics that will guide him during model development, including the extent to which the letter approximate the former. Stating this explicitly can prevent cases where the consumers of the models being developed - product and business people - understand only during or after model development that the wrong metric was optimized.
General remarks on scoping
In many places this phase is skipped, with the data scientist eager to start digging at the data and explore cool papers about possible solutions; in my experience, this is almost always for the worst. Skipping this phase can result in long weeks or months spent in developing cool models that end up not answering a real need, or failing in a very specific KPI that could have been explicitly defined with some premeditation.
2. The Research Phase
2.1. Data exploration
This is where the fun starts! The main advantage of having this phase commence after scoping is that our exploration can now be guided by the actual hard KPIs and model metrics we have decided on.
As always, there is a balance to be struck here between exploration and exploitation; even when having clear KPIs in mind, it is valuable to explore some seemingly unrelated avenues to a certain degree.
By now the initial set of required data should have been made available by data engineering. However, some deficiencies in the explored data will often be discovered during this phase, and additional data sources might be added to the working set. The data engineer should be prepared for this.
2.2. Literature & solutions review
Both academic literature and existing code and tools are reviewed in this phase. Balance is again important; both between exploration and exploitation, and between diving into the intricacies of the material and extracting takeaways and possible uses quickly.
In the case of academic literature, the choice of how deep to go into aspects like formal proofs and preceding literature depends heavily on both the time constraints and the context of the project: Are we building a strong basis for a core capability of the company or devising a solution to a one-off problem? Do we plan to publish our work on the subject in an academic paper? Are you planning to become the team's expert on the topic?
For example, take the case where a data scientist embarking on a project to help the sales department better predict lead generation yield or churn feels he has only a shallow understanding of stochastic process theory, on which many common solutions to these problems are built. The appropriate response to this feeling can be very different; if he works for an algo-trading company he should definitely be diving into said theory, probably even taking an online course on the topic; if, on the other hand, he works for a medical imaging company focused on automatic tumor detection in liver x-ray scans, I'd say he should find an applicable solution quickly and move on.
For example, if the production environment only supports deploying Java and Scala code for backend uses and the solution is thus expected to be provided in a JVM language, the data scientist will have to go deeper into Python-based implementations he find even during this research phase, as going forward with them into the model development phase entails translating them to a JVM language.
Finally, while reviewing literature, keep in mind that not only the chosen research direction (or a couple of directions) should be presented to the rest of the team. Rather, a brief review of the field and all examined solutions should accompany the choice made, explaining the upsides and downsides of each direction and the justifications for that choice.
This is an important check to perform at this stage both because some data and software engineering can begin in parallel to model development. Additionally, a suggested solution might turn out to be inadequate or too costly in engineering terms, in which case thisWhen technical issues are considered before model development starts, the knowledge gained during the research phase can be used to suggest an alternate solution that might better fit technical constraints. This is another reason why the research phase must also result in some overview of the solution landscape, and not just in a single solution direction.
2.4. Scope & KPIs validation
Again, the product manager needs to approve that the suggested solution, now stated in more technical terms, meets the scope and KPIs defined. Possible technical criteria that usually have easily detectable product implications are response time (and its relation to computation time), the freshness of data and sometimes cached mid-calculations (which are related to querying and batch computation frequency), difficulty and cost (including data cost) of domain adaptation for domain-specific models (domains are most often clients, but can be industries, languages, countries and so on) and solution compostability (e.g. do data and model structures allow to easily break a country-wise model down to a per-region model, or compose several such models into a per-continent model), though many more exist.
The amount and complexity of setup required for model development to begin to depend heavily on the infrastructure and amount of technical support available to the data scientist. In smaller places, and in places not yet used to supporting data science research projects, setup might sum up to the data scientist opening a new code repository and firing up a local Jupyter Notebook server or requesting a stronger cloud machine to run computations on.
In other cases, it might entail writing custom code for more complex functionalities such as data and model versioning or experiment tracking and management. When this functionality is instead provided by some external product or service (and more and more of these are popping up these days), some setup in the form of linking data sources, allocating resources and setting up custom packages might follow.
3.2. Model development
The extent of what is considered the model to be developed here varies by company and depends on the relation, and the divide, between the model to be delivered by the data scientist and the service or feature to be deployed in production. The various type of approaches to this divide can perhaps be captured somewhat by considering a spectrum.
On one end of the spectrum lies the case where everything is the model: from data aggregation and preprocessing, through model training (possibly periodically), model deployment, serving (possibly with scaling) and continuous monitoring. On the other end lies the case where just the choice of model type and hyperparameters, and commonly also advanced data preprocessing and feature generation, is thought of as the model.
Your company's location on the spectrum can depend numerous factors: the data scientists' preferable research language; relevant libraries and open source availability; supported production languages in the company; the existence of a data engineer and devs dedicated solely to data science related code; and the technical capabilities and work methodology of your data scientists.
In case of very full-stack-y data scientist, combined with enough support from a dedicated data engineer and devs - or, alternatively, with enough existing infrastructure dedicated to the operation and automation of data lake-ing and aggregation, model serving, scaling and monitoring (and possibly also versioning) - the wider definition for a model can be taken, and an end-to-end solution can be used throughout most of the iterations on model development.
This usually means building the complete pipeline first, from data sources all the way to scaleable served models, with simple placeholders for data preprocessing, feature generation and the model itself. Iterations are then made on the data-science-y parts while keeping the context to what is available and deployable on the existing infrastructure.
This end-to-end approach can take more time to set up, and each iteration on model types and parameters make take longer to test, but it saves time later paid for in the productization phase.
I personally love it, but it's complex to implement and maintain, and it's not always appropriate. In that case, some parts of the start and the end of the pipeline are left to the productization phase.
should ic. This gives a rough estimate of progress and also allows the data scientist to decide when the model seems to be working well enough to warrant the overall KPI check. Do note that this can be misleading, as getting from 50% to 70% accuracy, for example, is much easier than getting from 70% to 90%
Figure 2: Model failure entails iteration, but an approaching failure might send you back to research
When tests show that a model is off the mark, we usually investigate it and its output to guide improvements. Sometimes, however, the gap in performance is very large, with different variations of the chosen research directions all falling short - an approaching failure. This might warrant a change in the research direction, sending the project back into the research phase. This is the aspect of data science projects that is hardest to accept: the very real possibility of backtracking.
3.4. KPIs check
In the more common case, the hard metric is a good approximation of the actual product needs, but not a perfect one. This phase is thus an opportunity to make sure that the softer metrics, that cannot be checked automatically, are also satisfied. This is done together with product and customer success. If you can additionally check the actual value to a customer directly- e.g. when working with a design partner - then it's the best guide you could find for your iterations.
For example, let's say that we're dealing with a complex task such extracting relevant documents, given a query, from a huge corpus. The team might have decided that to try and increase the quality of the result set, focusing on variance in content and topics of the returned documents, as clients feel the systems tend to cluster quite similar documents in top results.
Model development might have progressed with some measurable metric for content variance in the results set - each model is scored by how varied are the top 20 documents it returns, given a set of test queries; perhaps you measure overall distance between document topics in some topic vector space or just the number of unique topics or flatness of significant word distributions.
4.1. Solution Productization & Monitoring Setup
This phase, as mentioned earlier, depends on the approach to both data science research and model serving in the company, as well as several key technical factors.
Productization: In cases where research language can be used in production, this phase might entail adopting the model code to work in a scalable manner; how simple or complex this process depends both on distributive computing support for the model language, and the specific libraries and custom code used.
When research and production language are different, this might also involve wrapping the model code in a production language wrapper, compiling it to a low-level binary or implementing the same logic in production language (or finding such an implementation).
Monitoring: Finally, a way to is set up; in rare cases, when the source of production data is constant, this can perhaps be safely skipped, but I'd say that in most cases you can't be sure of the stability of the source data distribution. Setting up such a performance check, then, can help us to not only detect problems in the model that we might have missed during development and productization, but more importantly changes in the source data distribution above which the model operates - commonly referred to as a covariate shift - that can degrade, in time, the performance of a perfectly good model.
Take, for example, the case where our product is an app that detects skin marks and evaluates whether to recommend the user to go see a skin doctor. A covariate shift might happen in our data when a popular new phone goes to market, equipped with a camera significantly different from those present in our data.
If everything is set up correctly, then this stage can sum up to, hopefully, pushing a button to deploy the new model - and any code serving it - to the company's production environment.
Partial Deployment: It is possible, however, that in order to test the effectiveness of the model (for example, in reducing churn, or increasing average monthly spending per user), the model will be deployed to in a manner that only part of the user/customer base is exposed to it. This enables a direct comparison of the effect on any measurable KPIs between the two (or more) groups in the user base.
Another reason you might not want to deploy the model to everyone is if it was developed to answer the needs of a specific customer or a group of customers, or if it's a premium feature or part of a specific plan. Alternatively, the model might have some element of personalization per user or customer; this is can sometimes be achieved by actually having a single model which take customer characteristics into account, but sometimes entails actually training and deploying a different model for each customer.
Whatever the case, all these scenarios increase the complexity of deploying the model and depending on existing infrastructure in the company (e.g. if you're already deploying some of the product features to subsets of your customers) theyby your back-end team.
This phase is even more complex when the model is to be deployed on end-products, like user phones or wearables, in which case model deployment might only happen as part of the next app or firmware update deployed.
Generating Bias: Finally, all cases of partial deployment are actually a pressing issue to the data science team for another reason: this naturally introduces bias into the future data the model will start accumulating - the model will start operating on data by a subset of users with possibly unique characteristics. Depending on the product and the specific biased characteristics, t in the wild, and possibly on future models trained on data accumulated during this period.
For example, in the case of device update, users who updated their apps/firmware earlier tend to fall into certain demographics (younger, more tech-savvy, higher income, etc.).
I've added another KPIs check here because I think a solution cannot be marked as delivered before its performance and successful answering of product and customer needs has been validated after deployment and actual use.
4.4. Solution delivered
Users and customers are happy. Product people have managed to build or adapt the product they wanted around the model. We're done. Toasts are toasted, cheers are cheered, and all is well.
The solution is delivered, and I would call the project done at this point. It does, however, keeps on living in a specific way - maintenance.
Having set up health checks and continuous performance monitoring for the model, these can trigger up short bursts of working on the project.
This is a suggestion for the flow of data science projects. It is also very specific, limited in scope - for the sake of simplicity and visibility - and obviously cannot cover the many variations on this flow that exist in practice. It also represents my experience.
For all of these reasons, I'd love to hear your feedback, insights,.


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This page shows the publications Philip Larsen has written about 3' Untranslated Regions.
The mRNA structure has potent regulatory effects on type 2 iodothyronine deiodinase expression. Mol Endocrinol. 2002 Jul; 16(7):1667-79.


Within 10 days of application submission, both the student traveler and one partraveler’s eligibility for the grant.
Once all the above steps have been completed and documents returned to the Jewish Federation, the trip provider will be paid the amount specified on the "GRAND TOTAL" line—up to $5,000, depending on the cost of your program. Payment to the trip provider can occur only after all forms are received and may take several weeks to clear. Please allow appropriate time.


Physicians, staff good for recovery
I have been lucky to have very skilled surgeons, and the back-up from physical therapy made for a quicker recovery.


Since 2011, the Pembroke Regional Hospital became a satellite location for the Ottawa Regional Cancer Centre, allowing residents of the Ottawa Valley to undergo surgery and receive cancer treatments closer to home. But the space requires upgrades as it was not originally designed for this program. The funds raised though the Cancer Care Campaign will allow the hospital to update and expand the chemotherapy and sterile room and medical day care units in tower D as well as the in-house pharmacy, located in one of the oldest parts of the hospital in tower A, where the chemotherapy medications are prepared.
He added the upgrades to the pharmacy are most urgent and will be taking place while the funds are being raised, with a goal of having that phase completed during this calendar year.
As for the tower D renovation, the plans are for more space to accommodate the growth so patients can easily be viewed by staff from a central location for safety purposes, and improved waiting areas with new furnishings with a focus on comfort.
For more information on the Cancer Care Campaign or to make a donation, visit https://prhfoundation.com/cancercare/.


As most of you know, I have a tendency to be “ahead of the curve” in a lot of my writing and research. I have been researching both Chaos Theory and Happiness for years, and wanted to review some of my past findings with you – because the world is catching up with some of the trends I saw coming a number of years ago, as written about in the Career Planning and Adult Development Journal:
Integrating the Chaos Theory and Positive Psychology came as an instinctive response to finding a way to help my clients solve their career issues. My purpose in suggesting the study of these two fields to my colleagues was the realization that a basic (not necessarily a deep) understanding of the fields of physics and psychology is essential. Both of these are now generating cutting edge concepts which are moving from their original narrow science subject to countless other applications. Read More→
Green Careers – Client Perspectives
Updated perspectives on Green Energy and Its Impact
Current Careers in Energy – What It Means to Be Green
“The future is uncertain . . . . but this uncertainty is at the very heart of human creativity.” According to Ilya Prigogine, Nobel Prize winner in 1977 and author of Order Out of Chaos, and The End of Certainty. This uncertainty and the necessity for creativity is exactly where we are in our energy world today!
Though I am a long time career consultant and confirmed futurist, providing the last word on green careers pushed me to use my more experienced clients and contacts as resources. My company, Career Design, sponsors Pathfinders for the Future, to provide career information and mentoring sessions on careers and for the past six months we have focused on the energy field. Authorities from varying energy areas have presented programs which were all videoed for others to view later at no charge. As a result, Bruce Thomas, a former marketing professional in radio & TV and an early retiree seeking his next career, initiated a non-profit organization, North Texas Advanced Energy Collaborative (NTAEC), dedicated to the development of North Texas as an economic and innovation zone for advanced and emerging energy technology industry. This is a rapidly growing group focusing on collaborative business development and launching a website in May for posting articles and information statewide, nationally and worldwide.
I have asked two members of this group to write a brief summary of their insight and possible opportunities and challenges for careers in this exploding industry:
“What is “Green” is by Tony Robinson, M.S. He has been in the construction industry since 1979. Tony spent more than twenty-five years working on the design and development of energy efficient building products.
The 2nd submission, “Profitable Green Solutions” is by Eric Woodroof, Ph.D. He has been in the energy efficiency and environmental field for over 15 years, helping businesses and governments reduce their environmental impact. Dr. Woodroof serves on several advisory boards for professional associations.
Five Points to Consider at Midlife (From Don’t Stop the Career Clock)
Just as there is no automatic system to successfully guide our career for us, there is no prescription for how we are to live our later life. Society and its institutions and professionals are trailing at least ten years behind in dealing with the process and problems of integrating aging and working.
Those of us who are embarking on our first or second midlife are asking ourselves some critical questions: What is the purpose of our later years? Does aging have any intrinsic purpose? Is there work to be done after rearing children? What are the rules, rights, and responsibilities of older people? What are the strengths and virtues of old age? What is a good old age? Who can teach us how to grow old well? How can we deal best with time? Can we expect new thresholds to cross as long as we live?
Regardless of our chronological age, the most meaningful thing we can live for is to reach our full potential. We must find and develop the skills we enjoy using and pursue a positive idea of aging. And we must keep on a growth and learning curve. Read More→
Identify Your Success Criteria for Career Satisfaction and Success
By Dr. Helen Harkness
Psst – Want the secret of “How to Create Career Satisfaction?”
Know What You Want From Your Career
Seems simple, right? It’s not that simple, but that is where the secret comes in. Career Design (CDA) has successfully helped countless clients transition their career since the ‘70s. They go through an in-depth self-exploration process to identify skills, interests, motivation, talents and much more.
One of the things all CDA clients do is identify their Success Criteria, which is a guide for them to use as they make decisions, especially those that relate to their career life and its effect on their personal life. Read More→
Make a New LIFE Resolution: Find Your Purpose. . .
Find Your Purpose You Can Pursue with Passion As Long As You Live!
It’s a New Year and now is the time for finding meaning in your life and work! This is exactly what CDA client, B.A. Norrgard, set out to do in February 2012. She started her journey of self-exploration with a battery of CDA Career Assessments and participating in the In-depth Skills Identification Workshop Series that countless Career Design clients have found to be one of the most insightful processes to add value to your life and work.
B.A., a woman of action, is making her mark on the tiny house movement in Dallas with a big splash! In December, she was interviewed by the Dallas Morning News and featured on the front page of the Sunday edition. Read the story here.
Dr. Harkness is Blazing a Trail to Fulfillment
Dr. Harkness was recently interviewed by Hanah Cho, Staff Writer for the Dallas Morning News and featured in the Senior Living Section. Dr. Harkness shared the story with Hanah of how she started Career Design Associates, Inc. back in 1978.
Now at 85, Dr. Harkness tells Hanah, “I don’t sweat my chronological age. Forget the clock. Focus on your functional age”. She will continue to blaze her trail to fulfillment for the next 20 years.
As Dr. Harkness says “Live Long and Die Fast”!
Guest post by Lissa Duty, a Dallas based Social Media Coach, who can attest to Dr. Harkness’s passion for helping career clients. Lissa, after being the long time office manager and administrative assistant at Career Design Associates, Inc. found her passion and opened her social media coaching and consulting practice in 2009.
Stop Aging in the Workplace! 4 Ways to Defy the Myths of Aging
Shattering the Mindless Myths & Misinformation of Aging is one of the greatest challenges for the Baby Boomer Generation!
Develop an innovative model integrating aging and working based on current research and rapidly shifting environmental realities
Realize that today’s model for aging and working can be destructive, deplorable, depressing, and invalid; and that redesigning and implementing a new pattern is essential.
Shatter the stereotypes and recognize the myths, misinformation, and negative effects of ageism in our society, workplace, and ourselves.
Know that age does not automatically spell decline.
Aging Myths: Physical – growing up/running down; Mental – shrinking brain; Psychological – nothing to live for; Creative – wilting inventiveness.
Congratulations Are In Order! Career Coach, Helen Harkness Inducted into the Hall of Fame!
Dr. Harkness Inducted into West Virginia University Education Hall of Fame
This past week career coach and career counselor, Helen Leslie Harkness, Ph.D. was one of four others recognized by The West Virginia University College of Education and Humans Services.
At the Hall of Fame reception, Dr. Harkness was inducted by Carolyn Atkins, Chair of the Selection Committee. Carolyn said “By recognizing these well-respected individuals, we emphasize the value we place on a strong work ethic, intelligence, creativity, motivation and achievement.
Five Tips to Change Your Career
The Five Tips to Change Your Career
Do you read the Dallas Morning News “Five” column? In this popular column by staff writer, Hanah Cho, local experts provide five recommendations on a topic useful to small business owners and individuals. Read More→
Categories : Latest Thoughts From Career Design Associates
Jeff Brady – Brand Echonomics
As many of you may know I am an avid reader. I will sit down with my pen, paper and a book and start to read and write. I take notes about every book I read. This helps me to recall them easier, but also serves as a reminder of the things I need to take action on.
I recently read Brand Echonomics: Building a Message that Matters by Jeff Brady. Jeff is a former news anchor for WFAA and is currently host of The Texas Daily. In addition, he owns public relations firm in Dallas, Brady Media Group, that focuses on storytelling for big brands.
My message to all about this book is that you need to read it to understand how to create your Brand ECHO, not only for business owners but as an individual. Storytelling is the major key to success in your personal and professional life. You tell your story to others and they amplify your story to others creating the echo. We all need more story tellers!!
Below are some of my notes from reading Jeff’s Book, Brand Echnomics and I highly recommend you read it to get the rest of the story.
Dr. Harkness on Pathways
Nancy Wiese on Fulfilling a Need
The best first step you can take to gain insight and sound information for your next career move. In Level 1 of our comprehensive career change services, CDA generates the Career Design profile from your answers to a series of validated, well-researched vocational assessment tools to provide you with a greater understanding of skills, interests, values, motivations and personality to match compatible careers. More information


By Jinia Shawdagor on June 15, 2018
In his pre-written remarks, Hinman said that based on his understanding of Ether, the entire networks, and the decentralized nature, allHinman also took the opportunity to refute the idea that a utility token could also fail to be a security. He said that even when a digital asset with a utility functions only as a means of exchange, it could be sold as an investment strategy. This would thus make it a security.
Mr. Hinman also informed the attendees that other crypto could still be considered securities. He said that a token by itself was not a security. However, the expectation of the buyer during the sale could be used to determine whether it was a security or not. He said that if a purchaser had a reasonable expectation that they could make a profit from the purchase, based on the actions of the seller, it is then a security.
He made it clear that the SEC was open to working with ICOs and their legal advisors to establish if a project should be registered. This is a sentiment, which has been expressed by many other SEC officials.
This announcement by the official will clear a major obstacle for the establishment of Ether’s future. This is something that the COO and President of Cboe Global Markets Inc, Chris Concannon has been considering since the launch of Bitcoin futures in December 2017. Since last year’s surge in the price of crypto, financial regulators have intensified their crackdown on the crypto world.
What do you think about this surprise declaration by HinmanECSecurity Exchange CommissionWilliam Hinman


Of unprecedented retrospective reach in Europe, this immersive exhibition is based on the work of the filmmakers constituting this movement and, particularly, on the photographic and artistic practice by Ben Caldwell, one of the most emblematic figures of this generation, holding an impressive career as an arts’ educator and independent director.
Stemming from the historical context of the african-american demonstrations for civil rights’ equality, the conquests, personalities and key-productions of L.A Rebellion are introduced. Ben Caldwell’s documental contributions - traces of the collaborative spirit of the filmmakers while shooting seminal L.A. Rebellion films - and audiovisual records of his artistic initiatives in the L.A. community will punctuate the exhibition space. Hence, the museum’s rooms should make an essential contribution to the contextualization of the films planned for this cycle of LEFFEST 2022 - to be watched in Cinema Nimas, in Lisbon - and elucidate the revolutionary essence of this movement, with social and aesthetic repercussions beyond L.A. Rebellion’s temporal boundaries.
Conversation: Where are you now, John Malkovich?
Conversation: The Gaza Strip, an open-air prison?


I had a few different jobs like working in the Marks and Spencer bakery, working in the café in Waitrose and temping in a pension company before joining Specsavers. I was also doing some exams in basic accounting to increase my knowledge in that area.
I am currently a tax accountant managing a team of four people. This is a new role that I have only been doing for a few months.
I run daily KPIs, do some training, attend meetings, do emails and assist the team with issues they face. I am also do ad-hoc projects when I have free time.
In my five years at Specsavers I have managed to complete an accounting qualification and have gone from an administrator in my first role to a manager in my current role.
I was able to attend college courses that were paid for by Specsavers, and I was able to take time off to study and take exams. My managers were flexible with study days and supported me when I needed extra help whether that was giving advice or letting us take a longer lunch to go to college to sit with one of the tutors when something wasn’t making sense.
I have recently changed role because I wanted to take on a new challenge, I had been in my previous team for almost 5 years, so it was time to try something new. I am currently learning about the world of tax and even though it is very challenging to learn a whole new job I am enjoying it.
Energetic, ever-changing and engaging.
If you work hard there are a lot of opportunities to develop and grow within the company. It is a really nice environment and the people are great.


We’re big fans of anything which encourages young learners to read and write, so we’re excited about the BBC’s 500 Words short story competition. The winners will be announced this Friday, so if you haven’t heard of 500 Words, here’s the info…