Data Science Weekly - Issue 82
Issue #82 June 18 2015
Editor Picks
MachineLearning uses NeuralNets & learns to play Super Mario from Scratch
MarI/O is a program made of neural networks and genetic algorithms that kicks butt at Super Mario World...
Deep Learning Machine Beats Humans in IQ Test
Computers have never been good at answering the type of verbal reasoning questions found in IQ tests. Now a deep learning machine unveiled in China is changing that...
IBM Watson Analytics helps grind big data in unmanned coffee shops
IBM has worked with Revive Vending to create systems for unmanned coffee shops that tap into the cognitive computing technology of Watson Analytics for data analysis. Three unmanned Honest Café coffee shops are in operation in London, and another four are in the pipeline...
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Data Science Articles & Videos
Recent Reports Make Machine Learning Sound Like a Sport. It isn’t
News that Baidu, the Google of China, cheated to take the lead in an international competition for artificial intelligence technology has caused a storm among computer science researchers. It has been called machine learning’s “first cheating scandal” by MIT Technology Review and Baidu is now barred from the competition...
Data is not the new middle manager
In April, the Wall Street Journal published article that claimed, as its title, "data is the new middle manager"...
Interview: J Babcock, Netflix on Discovery & Personalization from Big Data
We discuss the steps involved in Discovery process at Netflix, impact due to multitude of devices, system generated logs, and surprising insights....
Extending "Let It Go" with LSTM
Using recurrent neural network to generate piano music...
Machine Vision Algorithm Chooses the Most Creative Paintings in History
Picking the most creative paintings is a network problem akin to finding super spreaders of disease. That’s allowed a machine to pick out the most creative paintings in history...
A Tale of a Data Driven Culture
Slides from the Keynote @ Spark Summit, 2015: Gloria Lau VP of Data, Timeful (Acquired by Google)...
Bayesian Dark Knowledge
We consider the problem of Bayesian parameter estimation for deep neural networks, which is important in problem settings where we may have little data, and/ or where we need accurate posterior predictive densities, e.g., for applications involving bandits or active learning...
Kaggle Ensembling Guide
Model ensembling is a very powerful technique to increase accuracy on a variety of ML tasks. In this article I will share my ensembling approaches for Kaggle Competitions...
Rat Brain Robot
This robot is controlled by the brain of a rat - making it the world's first cyborg rodent...
Jobs
Data Scientist - GoDaddy - Sunnyvale, CA Our Domain Search and Recommendation team is looking for great scientists and engineers to join us in building and improving Domain Search at GoDaddy. Domain Search is one of the key strategic pillars of GoDaddy, with an important contribution to the company’s revenue, customer growth and innovation. As a data scientist, you would play a major role in improving the metrics of the search page across the 42 markets we support worldwide, and the add-on products and advertising we offer when the user searches for a domain...
Training & Resources
DataPyR: Curated collection of useful resources
DataPyR is an attempt to create a comprehensive curated collection of any and every possible useful resource for Python, R and data science...
Introduction to Hidden Markov Models
The lecture gives an overview on Hidden Markov Models (HMM), an ubiquitous tool for dealing with sequential data...
Fast Lomb-Scargle Periodograms in Python
The Lomb-Scargle periodogram is a classic method for finding periodicity in irregularly-sampled data. It is in many ways analogous to the more familiar Fourier Power Spectral Density (PSD) often used for detecting periodicity in regularly-sampled data. Despite the importance of this method, until recently there have not been any (in my opinion) solid implementations of the algorithm available for easy use in Python...
Books
Signal: Understanding What Matters in a World of Noise New release!...
"In Signal, I provide straightforward and practical instruction in everyday signal detection. Using data visualization methods, I teach how you can apply statistics to gain a comprehensive understanding of your data, which will serve as the context for signal detection. I then adapt the techniques of Statistical Process Control in new ways to detect not just changes in the measures but also significant changes in the patterns that characterize your data..."
For a detailed list of books covering Data Science, Machine Learning, AI and associated programming languages check out our resources page.
P.S. Interested in reaching fellow readers of this newsletter? Consider sponsoring! Email us for details :) - All the best, Hannah & Sebastian