Data Science Weekly Newsletter

MIT computer scientists can predict the price of Bitcoin
CSAIL/LIDS team's algorithm doubles initial investment in under 2 months...

AI Algorithm masters Space Invaders in All-Night Gaming Session
In a recent interview, Demis Hassaabis—founder of AI firm DeepMind, acquired last year by Google for over $500M —talked AI and showed video of one of his group’s deep learning algorithms killing it at Space Invaders...

Behind the Mic: The Science of Talking with Computers
Language. Easy for humans to understand (most of the time), but not so easy for computers. This is a short film about speech recognition, language understanding, neural nets, and using our voices to communicate with the technology around us...

Recognizing Stuff in Images with Deep Networks
The thing we’re really excited to show off with PARK or BIRD is our image recognition technology. To recognize 1000+ things, we employ a deep convolutional neural network...

Learning to Execute and Neural Turing Machines
I'd like to draw your attention to two papers that have been posted in the last few days from some of my colleagues at Google that I think are pretty interesting and exciting...

Building the LA Data Science Community: Szilard Pafka Interview
We recently caught up with Szilard Pafka, Chief Scientist at Epoch and Founder of Data Science LA. We were keen to learn more about his background, his role building the LA Data Science community and his work at Epoch...

Building a Data Science "Experiment Platform": Nick Elprin Interview
We recently caught up with Nick Elprin, Founder of Domino Data Lab. We were keen to learn more about his background, his thoughts on Data Science as a Service and the functionality he has built at Domino...

Deep Learning for Computer Vision with Caffe and cuDNN
This post serves to orient researchers, engineers, and machine learning practitioners on how to incorporate deep learning into their own work...

Using machine learning to rank search results (part 2)
How can we make ANNs fast enough to sort tens of thousands of products? What network structure should we pick? How long does it take to train a network? Are we using the right inputs?...

Automating Music Composition and Melody Generation
A program that learns music structure of given midi files and able to generate new melodies by judmental of other compositions. E.g. generate melody in style of Armstrong as negatively judged by Eminem and positively by Bach...

Daniel Roy on probabilistic programming and AI
Roy’s research focuses on theoretical questions that mix computer science, statistics, and probability...

Disney rendered its new animated film on a 55,000-core supercomputer
"This movie's so complex that humans couldn't actually handle the complexity. We have to come up with automated systems"...

Data Scientist, New York Times - New York City
The New York Times is dedicated to using data science to develop better products, make business decisions and reach larger audiences. We have click data, article text data, social network data, email data, subscription data, video data and mobile data available to us. We leverage this, along with statistical modeling and machine learning methods to find insights for high-level management and strategy, build API's for engineers, and create tools for editors and writers of the newsroom. The goal of this role is to help The Times reach a larger audience and develop a more engaged reader base...

A Tiny Julia Webservice
One benefit of using Julia for playing with statistics is that it's a modern, usable language for general purposes as well. Earlier I built a KNN classifier for predicting crime from the data on hbg-crime.org, so I thought it would be fun to build a web service in Julia that could return those results...

Latest D3 release
Bug fixes and performance improvements in today’s D3 3.4.13 release!...

Machine Learning: The Art and Science of Algorithms that Make Sense of Data
One of the most comprehensive machine learning texts around...
"This book really gives an fantastic overview of the theory of machine learning. I think combining this book with some of the online coursera courses for practical work would give anyone a really strong skill set backed up by the deeper insights..."...

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