Data Science Weekly - Issue 231
Issue #231 Apr 26 2018
Editor Picks
Why Is the Human Brain So Efficient?
How massive parallelism lifts the brain’s performance above that of AI...
Qualitative before Quantitative:
How Qualitative Methods Support Better Data Science
Have you ever been embarrassed by the first iteration of one of your machine learning projects, where you didn’t include obvious and important features? In the practical hustle and bustle of trying to build models, we can often forget about the observation step in the scientific method and jump straight to hypothesis testing...
Why I've lost faith in p values
There has been a lot written over the past decade (and even longer) about problems associated with null hypothesis statistical testing (NHST) and p values. Personally, I have found most of these arguments unconvincing. However, one of the problems with p values has been gnawing at me for the past couple years, and it has finally gotten to the point that I'm thinking about abandoning p values. ...
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Data Science Articles & Videos
Artificial Intelligence — The Revolution Hasn’t Happened Yet
"AI" has become a distraction -- not just to the general public, but also to computer scientists overly focused on imitating human intelligence...
The Book No One Read
Why Stanislaw Lem’s futurism deserves attention...
Toward the Jet Age of machine learning
Solving the challenges of efficiency, automation, and safety will require cooperation between researchers and engineers spanning both academia and industry...
Building An AI-Powered Society with AI Fund's Andrew Ng | Greymatter
In this episode of Greymatter, Greylock’s Sarah Guo and Dr. Andrew Ng, one of the foremost leaders in AI discuss AI and ML techniques being used in industry today, areas of ongoing research, how companies can leverage this technology, and the broader impact on the future workforce...
Storm damage to forests costs billions – here’s how AI can help
Europe loses as many trees to storms each year as Poland produces in timber. Until now, the models for predicting which trees are at risk have not been good enough...
Using machine learning to classify devices on your network
In this article, we plan to walk readers through using our machine learning code to classify devices on a network... we’ve experimented with classifying devices using packet-capture data...
Accelerating Deep Neuroevolution:
Train Atari in Hours on a Single Personal Computer
Today, we are releasing open source code that makes it possible to train deep neural networks to play Atari, which takes ~1 hour on 720 CPUs, now takes ~4 hours on a single modern desktop...
Lessons from My First Two Years of AI Research
A friend of mine who is about to start a career in artificial intelligence research recently asked what I wish I had known when I started two years ago. Below are some lessons I have learned so far. They range from general life lessons to relatively specific tricks of the AI trade. I hope others find them useful...
Jobs
Data Scientist / Statistician - Warby Parker - NYC
Warby Parker’s Data Science team develops tools to help our company make better decisions. Since Warby Parker is vertically integrated, with a strong retail and e-commerce business, there are a lot of places for statistics and machine learning to improve how we operate.
As a Data Scientist / Statistician you’ll lead one to three projects at a time, working closely with our Product Manager and other Data Scientists to bring your project to fruition. You’ll spend time talking to people in other parts of the business, using your knowledge of math and statistics to model their challenges and make their problems amenable to being aided by data...
Training & Resources
Tell PyTorch To Do An In Place Operation
Learn how to tell PyTorch to do an in-place operation by using an underscore after an operation's name, via a screencast video and full tutorial transcript...
Modern Pandas Part 8: Scaling pandas
As I sit down to write this, the third-most popular pandas question on StackOverflow covers how to use pandas for large datasets...
A Gentle Introduction to Neural Networks for Machine Learning
Top 10 Neural Network Architectures You Need to Know...
Books
The Theory That Would Not Die:
How Bayes' Rule Cracked the Enigma Code, Hunted Down Russian Submarines, and Emerged Triumphant from Two Centuries of Controversy An enjoyable account of the history of Bayesian statistics from Thomas Bayes's first idea to the ultimate (near-)triumph of Bayesian methods in modern statistics...
For a detailed list of books covering Data Science, Machine Learning, AI and associated programming languages check out our resources page.
P.S., Want to reach our audience / fellow readers? Consider sponsoring - grab a spot now; first come first served! All the best, Hannah & Sebastian