Data Science Weekly Newsletter

Issue

131

May 26, 2016

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Editor's Picks

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Autoencoding Blade Runner
In this blog I detail the work I have been doing over the past year in getting artificial neural networks to reconstruct films — by training them to reconstruct individual frames from films, and then getting them to reconstruct every frame in a given film and resequencing it ...

Soon We Won't Program Computers. We'll Train Them Like Dogs
Welcome to the new world of AI. Soon we won't program computers. We'll train them. Like dolphins. Or dogs. Or humans...

A Statistical Analysis of Minesweeper – Placing the Mines
I was recently asked in an interview to code a Minesweeper. It’s not really possible to code the entire game in a single run but there are some key elements to coding the game that can and probably should be memorized as they have other practical applications in computer science. In my minesweeper posts I'll share with you the important functions to coding the game but with a particular emphasis on the statistical aspect of the game...

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“The Science of Data-Driven Storytelling”

DataScience Inc. and the National Science Foundation’s West Big Data Innovation Hub have brought together leaders in academia, the non-profit sector, government, data science and publishing to discuss best practices for creating impactful data-driven stories. Click here to register
for the live-streamed workshop, “The Science of Data-Driven Storytelling”.

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Understanding Deep Dreams
In the last few months the Internet has been flooded with deep dreams: images augmented by neural networks which look incredibly trippy. Deep dreams have the potential to become the new fractals; beautifully backgrounds everyone knows are related to Maths, but no one knows really how. What are deep dreams, how are they generated and what can they teach us?...

Bridging the Gap Between Data Science and Data Engineering
Josh Wills, Director of Data Engineering at Slack, gives an awesome keynote at DataEngConf SF16...

Let Me Hear Your Voice and I’ll Tell You How You Feel
As part of my offline emotion sensing hardware (Project Jammin), I have already built early prototypes of facial expression and speech content recognition for emotion detection. In this short article I describe the missing part, a voice tone analyzer...

The Changing American Diet
See what we ate on an average day, for the past several decades...

100 Burritos in San Diego
A 10-dimensional system for rating the burritos in San Diego...

One Chart, Twelve Charting Libraries
Charting Libraries. Gosh, there are so many out there. On Wikipedia and other websites, one can find a comparison of ca. 50 libraries – and these are only JavaScript libraries; not mentioning languages like Processing and libraries for Python and R. In the following blog post, I will try to get to know a few ones out of the great sea of possibilities. I want to understand their differences and how easy it is to learn them. To do so, I created the same bubble chart with twelve different frameworks...

Terrapattern: A Prototype for Visual Query-by-Example in Satellite Imagery
We present the alpha version of Terrapattern: "similar-image search" for satellite photos. It's an open-source tool for discovering "patterns of interest" in unlabeled satellite imagery—a prototype for exploring the unmapped, and the unmappable...

Latent Semantic Indexing: How I Built PUBmatch.co
I thought I'd write up an explanation of how Latent Semantic Indexing works since I used it in my most recent project PUBmatch.co...

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Machine Learning Data Scientist - Gilt Groupe - New York
You will be joining the Personalization and Machine Learning team to build the algorithms and services that customize the Gilt member experience from sale notifications to product recommendations. We are an agile, product-driven, initiative-based team crafting the next generation of fashion personalization algorithms. We use our customer’s behavior to gain deeper insights into our members’ preferences, extract new information from product images and descriptions, and find the best ways to serve as personal stylists for our fashion-savvy customers...

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Setting up a Deep Learning Machine from Scratch
A detailed guide to setting up your machine for deep learning research. Includes instructions to install drivers, tools and various deep learning frameworks...

Python Tutorial
Python tutorial for data analysis that's geared toward complete beginners with no analysis or programming experience. ...

Learning to Love Bayesian Statistics
Thanks everyone for joining me for this webcast. I’m Allen Downey and I’m a professor at Olin College, which is a new engineering college right outside Boston. Our mission is to fix engineering education, and one of the ways I’m working on that is by teaching Bayesian statistics...

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The Lady Tasting Tea:
How Statistics Revolutionized Science in the Twentieth Century An insightful, revealing history of how mathematics transformed our world...
"I have taken courses in statistics, taught it many times and solved several statistical problems that have appeared in journals. But until I read this book, I never really thought about it in so deep and philosophical a manner..."... 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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