Data Science Weekly Newsletter

Teaching an AI to write Python code with Python code
OK, let’s drop autonomous vehicles for a second. Things are getting serious. This post is about creating a machine that writes its own code. More or less...

Mobile Phone Data Reveals Literacy Rates in Developing Countries
A machine learning algorithm has learned to tell whether individuals can read or write by analyzing their mobile phone records...

Machine Learning Algorithm Spots Depression in Speech Patterns
Researchers from the University of Southern California have developed a new machine learning tool capable of detecting certain speech-related diagnostic criteria in patients being evaluated for depression...

Where science and policy change the world. And You.

Apply your knowledge & skills to federal policy via the AAAS Science & Technology Policy Fellowships. A year-long professional development opportunity for doctoral level data scientists to serve in the federal government in Washington, D.C.
STPF fosters a career-enhancing network of science leaders who understand policymaking & contribute to society...

What's Being Built With Deep Learning?
Applications built using deep learning seems to be straight out of science fiction. Here is a partial sample of some of the incredible applications that have been developed so far...

It's ML, not magic: simple questions you should ask to help reduce AI hype
This post aims to outlay a few simple rules that, without restricting one's ability to "dream big", should be able to cull the most ludicrous examples of AI-prefixing...

Is This Time Different? The Opportunities and Challenges of AI
Remarks at AI Now: The Social and Economic Implications of Artificial Intelligence Technologies in the Near Term...

This mind-blowing photo app makes Instagram’s filters look so lame
By using a combination of neural networks and artificial intelligence, the end results are a real sight to behold. It doesn’t just put a filter over your image, it actually scans the data to apply the style in an impressive way...

Meet the data scientist plotting Twitter’s revival
Data science influences decisions large and small at Twitter. Aside from the new team, Twitter has roughly 30 data scientists – out of 3,800 employees – sitting in San Francisco. “We are a small team. But by understanding our users, we can change the course of the company,” Linus tells me...

Home Depot Product Search Relevance, Winners' Interview
A total of 2,552 players on over 2,000 teams participated in the Home Depot Product Search Relevance competition which ran on Kaggle from January to April 2016. Kagglers were challenged to predict the relevance between pairs of real customer queries and products. In this interview, the first place team describes their winning approach and how computing query centroids helped their solution overcome misspelled and ambiguous search terms...

Thinking in SQL vs Thinking in Python
Over the years, I’ve used a variety of languages and tools to analyze data. As I think back on my time using each tool, I’ve come to realize that each encourages a different mental framework for solving analytical problems. Being conscious of these frameworks—and the behaviors they promote—can be just as important as mastering the technical features of a new language or tool...

The Theorem Every Data Scientist Should Know (Part 2)
Last week, I wrote a post about the Central Limit Theorem. In that post, I explained through examples what the theorem is and why it’s so important when working with data. If you haven’t read it yet, go do it now. To keep the post short and focused, I didn’t go into many details. The goal of that post was to communicate the general concept of the theorem. In the days following it’s publication, I received many messages. People wanted me to go into more details.Today, I’ll dive into more specifics...

Data Scientist - Hulu - Santa Monica, CA
Data Science Team at Hulu combines deep data analysis and research of our rich user data to present a compelling vision around user retention and preferences across the vast ecosystem of Hulu’s product offerings and content. We are looking for data scientists who are passionate about using data to drive strategy and product recommendations. You will be engaged with senior leaders to design well-constructed analyses and work cross-functionally with analysts, product managers and engineers to effectively deliver actionable results. You will work on variety of domains such as data science, machine learning and optimization; lead cutting edge analytical solution development pipeline and contribute to external research via attending conferences and collaborations...

Building Machine Learning Estimator in TensorFlow
Have you ever wondered what’s the magic behind the tutorials on Large-scale Linear Models and Wide & Deep Learning? I hope this post would at least point you to the right direction...

How to Start Learning Deep Learning
Due to the recent achievements of artificial neural networks across many different tasks (such as face recognition, object detection and Go), deep learning has become extremely popular. This post aims to be a starting point for those interested in learning more about it...

Altair
Declarative statistical visualization library for Python. Altair's API is simple, friendly and consistent and built on top of the powerful Vega-Lite JSON specification. This elegant simplicity produces beautiful and effective visualizations with a minimal amount of code...

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...

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