Data Science Weekly Newsletter

Issue

117

February 18, 2016

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Editor's Picks

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Why You Should Stop Worrying About Deep Learning And Deepen Your Understanding of Causality Instead
Everywhere you go these days, you hear about deep learning’s impressive advancements. This post discusses an often-overlooked area of study that is of much higher relevance to most data scientists than deep learning: causality...

Highly Effective Data Science Teams?
For all its hype, Data Science is still a pretty young discipline with fundamental unresolved questions. What exactly do data scientists do? How are data scientists trained? What do career paths look like for data scientists? Lately, I’ve been thinking most about a related question: What are the markers of a highly effective data science team?...

TensorFlow Chessbot
A TensorFlow Convolutional Neural Network algorithm trained on 32x32 grayscale chess tiles predicts chessboards layouts from online chessboard screenshots...

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Share actionable SQL queries with anyone in your company
Mode is a online analytics suite built by analysts, for analysts. It brings together SQL, charts, and dashboards in one central place. Stop wasting time on repetitive data pulls and begin tackling meaningful exploratory analysis. Start your free trial today!

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What BuzzFeed's Dao Nguyen Knows About Data, Intuition, And The Future Of Media
To understand what makes BuzzFeed tick, you need to know how Dao Nguyen thinks about data...

Robot Art Raises Questions about Human Creativity
What is the potential of machine art, and can it truly be described as creative or imaginative?...

Machines and Metaphors
When an algorithm is taught to paint the Mona Lisa in the style of van Gogh’s Starry Night, it doesn’t just demonstrate an ability to paint like van Gogh; it demonstrates a much more general ability to emulate human behavior...

Training a Recurrent Neural Network to Compose Music
After seeing the wonderful things RNNs can do, I decided to try and use them to tackle a problem I’ve been interested in for years: programmatic music composition...

A Conversation Between Two AIs
The other day, I was introduced to Jason at Clara Labs, a startup whose product is an AI personal assistant to schedule meetings. As it so happens, I use x.ai, a startup whose product is also an AI personal assistant to schedule meetings. We wanted to meet for coffee, so I decided to let our AIs work it out...

Around the World in 60 Days: Getting Deep Speech to Work in Mandarin
At SVAIL (Silicon Valley AI Lab), our mission is to create AI technology that lets us have a significant impact on hundreds of millions of people. When we did the original Deep Speech work in English, it became clear that the shortest path to achieving our mission would be to get the system working in Mandarin Chinese...

Why I use ggplot2
If you’ve read my blog, taken one of my classes, or sat next to me on an airplane, you probably know I’m a big fan of Hadley Wickham’s ggplot2 package, especially compared to base R plotting. Not everyone agrees. Among the anti-ggplot2 crowd is JHU Professor Jeff Leek, who yesterday wrote up his thoughts on the Simply Statistics blog:...

2 Highly Effective Ways to Estimate User Location in Social Media
The 140 characters in a tweet don’t leave much room for context. To understand a tweet, you often need to understand the who, what, and where behind it. The lab’s Soft-Boiled challenge spent some time looking at the "where," taking an automated approach to estimating the location of users or messages on Twitter (a problem referred to as geo-inferencing)...

Data scientists mostly just do arithmetic and that’s a good thing
Hi, I’m Noah. I work at Basecamp. Sometimes I’m called a “data scientist.” Mostly, I just do arithmetic, and I’m ok with that. Here’s a few of the things I worked on in the last couple of weeks, each of them in response to a real problem facing the business...

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Data Scientist - Analytical Flavor Systems - State College, PA
Build the next generation of predictive quality control and production optimizations tools for the food and beverage industry. Analytical Flavor Systems uses machine learning and artificial intelligence to build predictive and real-time Quality, Process, and Market Intelligence services to create decision metrics at each stage of a product's life-cycle. We leverage our predictive models across products & industries for flavor profile optimization, production process optimization, demographic targeting & cognitive marketing - helping companies create and sell the best product to their highest value consumers with every batch...

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torch-rnn
torch-rnn provides high-performance, reusable RNN and LSTM modules for torch7, and uses these modules for character-level language modeling similar to char-rnn...

Statsmodels’s Documentation
statsmodels is a Python module that provides classes and functions for the estimation of many different statistical models, as well as for conducting statistical tests, and statistical data exploration...

Laboratory!
A Python library for carefully refactoring critical paths (and a port of GitHub's Scientist)...

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Introduction to Algorithms Comprehensive textbook covering the full spectrum of modern algorithms
"I have studied algorithms using several books, and this is by far the best..."... For a detailed list of books covering Data Science, Machine Learning, AI and associated programming languages check out our resources page...

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