Weekly Machine Learning drop #2

I’ve become more and more interested in machine learning in last year. This is my way of collecting and sharing interesting reads on topic I stumble upon. They will be arranged in few categories. Those posts will be published each Friday and format will evolve.

In this part I share interesting news from machine learning and artificial intelligence world. Those are mostly not very scientific articles about interesting applications,  predictions and controversies that AI causes.

Some of those are not “news” anymore, as I have a long backlog of them saved. They are all very interesting though!

The Great A.I. awakening.
Fascinating (and long) read on how Machine Learning drastically changed backends of Google services. If you are to read only one article from this week’s drop, pick this one.

Future of Finance
AI and Bitcoin are driving next generation of hedge funds. Read about how technology changes financial market.

“Ross” is AI Lawyer
Lawyers are expected to be one of the jobs to be replaced by AI. Algorightms are much better in going through complicated laws and precedences and drawing logical conclusions from set of rules. Ross is already doing great job as paralegal.

The AI Takeover Is Coming
Author is exploring more positives sides of incoming AI revolution. Instead of fearing the machine, let’s Embrace It.

I pick one or two videos every week that touches interesting subject in AI and ML field. Some time it’s more scientific and the other it’s about real life applications.

Tensorflow Dev Summit 2017
This is whole playlist for this year’s Tensorflow Summit. It took place in mid February in Mountain View, CA. Talks on ecosystem, distributing calculation, building models or art generation. Pick what interests you :)

Learning materials
Here I’m sharing material for learning machine learning that I found useful – online courses, blogs, books etc. This is gonna be rather technical stuff.

MIT 6.034 Artificial Intelligence lectures
23 lectures from MIT, going through many AI algorithms and methodologies. Most of them are from Fall 2010, but some have been updated with versions from later years to include new advances in areas like Neural Networks.

Rules of ML
Google’s guidelines for developing Machine Learning systems. Slightly technical (but on high level) document presenting how Google approaches designing AI products.

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