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Update #92 - WK4 of 2019

Unlike every year, I didn't send out an e-mail to all the people in my list due to GDPR. So it seemed
Update #92 - WK4 of 2019
By Dries Bultynck • Issue #92 • View online
Unlike every year, I didn’t send out an e-mail to all the people in my list due to GDPR. So it seemed, that shouldn’t have been an reason as this is “business” related. Kinda. So I sent out an update on Linkedin few weeks ago.
So … like any other previous newsletter, here’s what triggered me to read this week:

How's Belgium Doing?
Always interesting if we do well compared to the other OECD countries, don’t you think? Work-life balance seems to be amazing, yet… why doesn’t it feel that way?
Pay my 'brand' Nike :)
Colin Kaepernick files to trademark image of his face, hair
Everyone wants your time / attention
Netflix says Fortnite is bigger competition than HBO or Hulu - Polygon
Banned from Facebook? So what ...
Facebook & AI
One of the most interesting blogs in the past few months, by far … the facebook research department sharing their attempts to work with machine learning techniques to solve items on big scale. Nothing society really needs or is waiting for … but building blocks for the next wave of AI to solve the real global problems (lets hope so).
The amount of data, capacity of computation & brains to process that information, should be obliged to contribute on a higher level. How? Tax the inertia of Data Capital to improve society! (more on that in Unlocking Intelligence In The Next Decade | DriesBultynck.com - half way the page)
If you want to read more, definitely check their year overview. And that was only 2018! Quite amazing stuff. They just use ML for just about anything!
AI year in review - Facebook Code
Research of my own
As I’m a bit bored by today’s marketing and the lack of data being used in decision making on all levels, triggered my to invest all my time into data & marketing analytics.
I’ve been deep diving into machine learning since april 2018 and have been working on some stuff on my own, such as trying to predict Facebook needed budget spend on ads based on historical data. Quite challenging, yet… it will happen ;-) hope to share this in a blogpost soon.
Building a model to predict
Building a model to predict
Evaluating outliers & data points
Evaluating outliers & data points
Evaluating features on their impact on the predictive model
Evaluating features on their impact on the predictive model
That’s it for this week.
d - out.
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Dries Bultynck

The internet is the best thing that ever happened to me. Really! It helps me to better understand the world we live in and learn as much as I can, as fast as I can in order to be Creative with Intelligence as wide as the box can get. @Parafixio is my playground.

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