Weekly Machine Learning drop #3

I’ve become more and more interested in machine learning during last year. This is my way of collecting and sharing interesting reads on the topic I stumble upon. Those posts are published each Friday, they are divided into few categories and the format is constantly evolving.

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!

Google acquires Kaggle
Kaggle is a platform for solving machine learning problems. As a company, you can publish your problem with sample dataset and pay people the or best solution of your problem. There are also practice tasks, for example analysing Titanic data. Last week Google bought Kaggle, most likely to access 800’000 community of machine learning developers.

Poker is another game, AI can beat humans in
Two independent researcher groups’ AIs managed to beat professional players in Texas Hold’em Poker, the most complicated version of poker. It’s another game at which computers are getting better.  Will those teams now play against each other?

Facebook wants to predict and prevent suicide attempts
Using machine learning and tens of thousands of reported posts, facebook build a model to predict people who plan to commit suicide. On a similar note, there is a map, that tries to predict crimes in London. Are we getting closer to Minority Report?

Is AI going to kill us all?
When you see a movie about AI, it usually tries to whipe out humanity. But there are also people thinking otherwise with solid philosophical arguments.

JPMorgan Software Does in Seconds What Took Lawyers 360,000 Hours
Big banks feeling more and more competition from fintech sector, are turning into ML to streamline their processes and help replace layers of redundant software.

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

AI experts panel from Beneficial AI conference
Watch Elon Musk, Ray Kurzweil, Nick Bostrom and few others discuss their outlooks for incoming artificial intelligence.

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

Google’s Depp Learning course on Udacity
This 3 months course goes through fundamentals of Deep Learning. Starting from building simple neural networks from a linear regression model, up to exploring Convolutional Neural Networks for image recognition and Long Term Short Memory algorithms for text analysis. It’s based on Tensorflow so basic knowledge of htis library will be helpful. It also assumes some basic knowledge in Machine Learning.

Pytorch tutorial on Github
Pytorch is another tensor-based python library for machine learning. It has its fans among the academic world and some upsides over Tensorflow.

This is it for today, thanks for reading. If you liked the post, let me know and please check other parts of the series.

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