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Weekly Selection – Jun 8, 2018

Automated Feature Engineering in Python

By William Koehrsen – 11 min read

Machine learning is increasingly moving from hand-designed models to automatically optimized pipelines using tools such as H20, TPOT, and auto-sklearn. These libraries, along with methods such as random search, aim to simplify the model selection and tuning parts of machine learning by finding the best model for a dataset with little to no manual intervention.


Intuitively Understanding Convolutions for Deep Learning

By Irhum Shafkat – 15 min read

The advent of powerful and versatile deep learning frameworks in recent years has made it possible to implement convolution layers into a deep learning model an extremely simple task, often achievable in a single line of code.


Python for Data Science: 8 Concepts You May Have Forgotten

By Conor Dewey – 7 min read

If you’ve ever found yourself looking up the same question, concept, or syntax over and over again when programming, you’re not alone. I find myself doing this constantly.


Using Deep Q-Learning in FIFA 18 to perfect the art of free-kicks

By Chintan Trivedi – 8 min read

In my previous article, I presented an AI bot trained to play the game of FIFA using Supervised Learning technique. With this approach, the bot quickly learnt the basics of the game like passing and shooting. However, the training data required to improve it further quickly became cumbersome to gather and provided little-to-no improvements, making this approach very time consuming.


How I Used Data Science and Machine Learning to Find an Apartment in Amsterdam

By Rafael Pierre – 11 min read

Amsterdam’s Real Estate Market is experiencing an incredible ressurgence, with property prices soaring by double-digits on an yearly basis since 2013. While home owners have a lot of reasons to laugh about, the same cannot be said of people looking for a home to buy or rent.


The Best Words

By Leon Zhou – 6 min read

Uttered in the heat of a campaign rally in South Carolina on December 30, 2015, this statement was just another of a growing collection of "Trumpisms" by our now-President, Donald J. Trump. These statements both made Donald more beloved by his supporters as their relatable President, while also a cause of ridicule by seemingly everyone else.


Must know Information Theory concepts in Deep Learning (AI)

By Abhishek Parbhakar – 6 min read

Information theory is an important field that has made significant contribution to deep learning and AI, and yet is unknown to many. Information theory can be seen as a sophisticated amalgamation of basic building blocks of deep learning: calculus, probability and statistics.


Light on Math Machine Learning: Intuitive Guide to Understanding Word2vec

By Thushan Ganegedara – 12 min read

Here comes the third blog post in the series of light on math machine learning A-Z. This article is going to be about Word2vec algorithms. Word2vec algorithms output word vectors.


Explaining the 68–95–99.7 rule for a Normal Distribution

By Michael Galarnyk – 4 min read

The normal distribution is commonly associated with the 68-95-99.7 rule which you can see in the image above. 68% of the data is within 1 standard deviation (σ) of the mean (μ), 95% of the data is within 2 standard deviations (σ) of the mean (μ), and 99.7% of the data is within 3 standard deviations (σ) of the mean (μ).


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