Data Science Weekly Newsletter

Issue

160

December 15, 2016

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Editor's Picks

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What Neural Network Can Tell About Your Doodles?
At this point in time, neural nets like Google’s “Quick, Draw,” are still learning to recognize people’s drawings. And that’s just the beginning. Soon they will be able to analyze them. Just like I did, but using bigger data...

Deep Learning Reinvents the Hearing Aid
Finally, wearers of hearing aids can pick out a voice in a crowded room...

Where Should Machines Go To Learn?
Past civilizations built grand libraries to organize the world’s knowledge. These repositories of information focused on cataloging, aggregating, organizing and making information accessible so that others could focus on learning and creating new knowledge. AI and machine learning systems also need repositories of information from which to learn — and right now everyone is building their own...

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Yhat

We built Rodeo
to make Python easier to use. It's open source & free. Support for Windows, Mac & Linux. Happy holidays! -The Yhat team.

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The Great A.I. Awakening
How Google used artificial intelligence to transform Google Translate, one of its more popular services — and how machine learning is poised to reinvent computing itself...

Traffic signs classification with Deep Learning
This is the second article in the self driving cars series. Goal: Classify traffic signs using a simple convolutional neural network...

Tourists Vs Locals: 20 Cities Based On Where People Take Photos
Tourists and locals experience cities in strikingly different ways. For example, in London most tourists will visit Buckingham Palace, the Houses of Parliament, St. Paul’s Cathedral, Oxford Street, etc. but will probably not end up visiting East Croydon, Hendon, Dagenham or any of the other parts of London outside of Zone 1...

Wall Street wants algorithms that trade based on Trump's tweets
President elect Donald Trump's ability to move the stock market with a tweet became readily apparent yesterday after an early morning tweet about Lockheed Martin's F-35 fighter jet program caused the company to lose $4 billion in market value. While that's a major loss for the company, it actually presents an opportunity for traders on Wall Street, some of whom have already started looking for ways to easily cash in on the volatility Trump brings to the market...

Type Safety and Statistical Computing
I broadly believe that the statistics community would benefit from greater exposure to computer science concepts. Consistent with that belief, I argue in this post that the concept of type-safety could be used to develop a normative theory for how statistical computing systems ought to behave...

Deep-Learning Machine Listens to Bach, Then Writes Its Own Music in the Same Style
Can you tell the difference between music composed by Bach and by a neural network?...

Visualizing taxi trips between NYC neighborhoods with Spark and Microsoft R Server
In this post, we will take a look at the RxSpark API for R, part of the RevoScaleR package and the Microsoft R Server distribution of R on HDInsight. We'll use RxSpark to visualize a dataset of 140M taxi rides between boroughs in New York City...

Data-derived Products
In this installment, I discuss some in-the-weeds approaches to creating data-derived products. For me, this means using metadata/logs, productized for a non-adjacent market and selling something of value. This requires technical, business and creative skills...

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Software Engineer / Sr Data Scientist - Slice Technologies - San Mateo, CA
Slice Intelligence is looking for a skillful engineer (or senior data scientist) to add to its Data Science team. Either a developer with some data science exposure and interest, or a senior data scientist with top coding and engineering skills and an interest to focus on development would be a fit. This Engineer is not someone to whom mundane tasks are tossed as a Doer in a Thinker / Doer dichotomy: Slice Intelligences Data Scientists and Engineers are both Thinker-Doers! So you wont be re-writing hopeless broken Python code into Java and/or scheduling ETL jobs...

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PyData, The Complete Works
The unofficial index of all PyData talks. This was intially going to be a pickled pandas DataFrame object, but then I decided against it. So here it is - in beautiful Github flavored markdown...

How to Train a GAN? Tips and tricks to make GANs work
While research in Generative Adversarial Networks (GANs) continues to improve the fundamental stability of these models, we use a bunch of tricks to train them and make them stable day to day. Here are a summary of some of the tricks...

End-to-end speech recognition with neon
The goal of the present exposition is to provide a relatively simple guide to using Neon to build a speech recognition system using “pure” DNNs...

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Guesstimation: Solving the World's Problems on the Back of a Cocktail Napkin
"Guesstimation enables anyone with basic math and science skills to estimate virtually anything--quickly--using plausible assumptions and elementary arithmetic"...

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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