Data Science Weekly Newsletter - Issue 121

Issue #121

March 17 2016

Editor Picks
   
 

A Message from this week's Sponsor:

 

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Data Science Articles & Videos

 
  • Diagnosing Heart Diseases with Deep Neural Networks
    The Second National Data Science Bowl, a data science competition where the goal was to automatically determine cardiac volumes from MRI scans, has just ended. We participated with a team of 4 members from the Data Science lab at Ghent University in Belgium and finished 2nd!...
  • Police Will Soon Be Watched by Algorithms That Try to Predict Misconduct. Is That a Good Thing?
    Police in Charlotte, North Carolina, are set to become guinea pigs for a new high-tech approach to improving relations between cops and citizens. The Charlotte-Mecklenburg police department is working with University of Chicago researchers to create software that tries to predict when an officer is likely to have a bad interaction with someone. The claim is that it will be able to forewarn against everything from impolite traffic stops to fatal shootings...
  • The Pressing Game: Optimal Defensive Disruption in Soccer
    Passing is a cardinal soccer skill and a key factor in strategy development; it helps the team to keep the ball in its possession, move it across the field, and outmaneuver the opposing team in order to score a goal. From a defensive perspective, however, it is just as important to stop passes from happening, thereby disrupting the opposing team’s flow of play. Our main contribution utilizes this fundamental observation to define and learn a spatial map of each team’s defensive weaknesses and strengths...
  • How to replace a pie chart
    The problem with a lot of pie-chart bashing (and most “chart-shaming,” in fact) is that people don’t follow up with a better alternative. So here I’ll show how I would have created a different graph (using R and ggplot2) to communicate the same information. This also serves as an example of the thought process I go through in creating a data visualization...
  • Introduction to Scikit Flow
    Scikit Flow is a simplified interface for TensorFlow, to get people started on predictive analytics and data mining. It helps smooth the transition from the Scikit-learn world of one-liner machine learning into the more open world of building different shapes of ML models...
  • Deep-Q learning Pong with Tensorflow and PyGame
    In a previous post we went built a framework for running learning agents against PyGame. Now we'll try and build something in it that can learn to play Pong. We will be aided in this quest by two trusty friends Tensorflow Google's recently released numerical computation library and this paper on reinforcement learning for Atari games by Deepmind...
 
 

Jobs

 
  • Director of Data & Analytics - Treehouse - Portland or Remote

    Treehouse brings affordable technology education to people everywhere in order to help them achieve their dreams and change the world. As Treehouse and its store of valuable data grows, we’re looking for a Director of Data and Analytics to lead both the data team and the data vision. You’d be leading a remote, cross-functional team of data scientists and engineers and guiding Treehouse’s choices around data architecture, engineering, and analytics as we scale. It’s a chance to do great, impactful work for Treehouse and the world!...
 
 

Training & Resources

 
  • Installing TensorFlow on Raspberry Pi 3 (and probably 2 as well)
    We did it! It took a lot of head-banging and several indirect passings-of-the-torch, but we finally got TensorFlow compiled and running properly on the Raspberry Pi! Hopefully this will enable more hardware-based machine learning projects, as well as making the distributed aspects of TensorFlow more accessible...
  • Using D3 To Add An SVG Element
    This video covers a) D3 Append Revisited, b) Setting Selection Attributes, c) Circle Example, d) D3 Style Operator, and e) D3 Legibility through JS variables...
 
 

Books

 

  • Code Your Own Neural Network: A step-by-step explanation

    This mini-book will take you step-by-step through coding your own neural network....

    "I thought this book was a great introduction to neural networks at a code level. By actually creating the thing I was able to get a decent understanding of how neural networks function..."

    For a detailed list of books covering Data Science, Machine Learning, AI and associated programming languages check out our resources page.
 
 
P.S. Interested in reaching fellow readers of this newsletter? Consider sponsoring! Email us for details :) - All the best, Hannah & Sebastian
 
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