Data Science Weekly Newsletter
Issue
122
March 24, 2016
Editor's Picks
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An unhealthy obsession with p-values is ruining science
Over the past couple of years, Stanford meta-researcher John Ioannidis and several colleagues have been working on a paper that should make any nerd think twice about p-values, those tests of statistical significance that are now commonly perceived as a signal of a study's worth...
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Twitter Facial Analysis Reveals Demographics of Presidential Campaign Followers
If you follow Hillary Clinton or Donald Trump on Twitter, your face has probably been analyzed by a machine to determine your age, ethnicity, and social influence...
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How real businesses are using machine learning
But from where I sit, running a company that enables a huge number of real-world machine-learning projects, it’s clear that machine learning is already forcing massive changes in the way companies operate...
A Message From This Week's Sponsor
Data Science Articles & Videos
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Five Lessons from AlphaGo’s Historic Victory
AlphaGo handily beat 18-time world Go champion Lee Sedol 4-1, and in doing so taught us several interesting lessons about where AI research is today, and where it is headed...
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Using Deep Q-Network to Learn How To Play Flappy Bird
This project follows the description of the Deep Q Learning algorithm described in Playing Atari with Deep Reinforcement Learning [2] and shows that this learning algorithm can be further generalized to the notorious Flappy Bird...
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“Eat, Rate, Love” — An Exploration of R, Yelp, and the Search for Good Indian Food
At Springboard, we pair learners with industry experts who help them learn data science. We help take learners all the way to a working portfolio project. This is a final project from one of our learners, Robert Chen...
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Preventing airline maintenance delays with R
Maintenance glitches cost US airlines 1.4 billion dollars in 2014. So airlines are naturally looking for ways to cut down on these costs, and minimize unexpected maintenance issues. This is a perfect opportunity to use predictive analytics: modern aircraft generate a wealth of data...
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Scraping the Web for Analytics Directors
In this post I’ll show you how you can scrape data from the web to build a data table of baseball analytics directors...
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Understanding Aesthetics with Deep Learning
The question then to ask is what do the master photographers’ images have in common, and what separates them from the amateur images? While it’s difficult for a computer to answer a philosophical question, if we express the question in mathematical terms we can attempt to solve it computationally...
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Deep Advances in Generative Modeling
In recent years, deep learning approaches have come to dominate discriminative problems in many sub-areas of machine learning. Alongside this, they have also powered exciting improvements in generative and conditional modeling of richly structured data such as text, images, and audio. This talk, led by indico's Head of Research, Alec Radford, will serve as an introduction to several emerging application areas of generative modeling and provide a survey of recent techniques in the field...
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Generative Image Modeling using Style and
Structure Adversarial Networks
In this paper, we factorize the imagegeneration process and propose Style and Structure Generative Adversarial Network...
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Tutorial: Web scraping and mapping breweries with import.io and R
Getting information on craft breweries can be a difficult process, with data dispersed over multiple websites or in formats unusable for analysis...
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How does Lumosity use data science?
I have been working on the data science team at Lumosity for about one and a half years. Let me tell you about some of the work we do...
Jobs
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Senior Data Scientist - Lumosity - San Francisco
The Data Science team at Lumosity works closely with our Product, Marketing and Science teams, leveraging data from over 80 million members and over 3 billion cognitive game plays to build compelling product features, support robust product experimentation and analysis, and support our scientific efforts. We’re looking for a self-starter who has experience working cross-functionally to deliver product features and improvements using data. Feel free to reach out to our team member Ryan
if you want to learn more...
Training & Resources
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Theano Tutorial
This is an introductory tutorial on using Theano, the Python library. I’m going to start from scratch and assume no previous knowledge of Theano...
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TensorFlow ConvNets on a Budget with Bayesian Optimization
In this post on integrating SigOpt with machine learning frameworks, we will show you how to use SigOpt and TensorFlow to efficiently search for an optimal configuration of a convolutional neural network (CNN)...
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Machine Learning: An In-Depth, Non-Technical Guide — Part 5
In this final chapter, we will revisit unsupervised learning in greater depth, briefly discuss other fields related to machine learning, and finish the series with some examples of real-world machine learning applications...
Books
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AI for Humans, Volume 3: Deep Learning and Neural Networks
Demonstrates neural networks in a variety of real-world tasks such as image recognition and data science...
"The content is easy to digest and not heavy on the math. Great primer to get used to concepts before diving deeper..."... For a detailed list of books covering Data Science, Machine Learning, AI and associated programming languages check out our resources page...