Data Science Weekly Newsletter

A Concise History of Neural Networks
The idea of neural networks began unsurprisingly as a model of how neurons in the brain function, termed ‘connectionism’ and used connected circuits to simulate intelligent behaviour...

AI’s Research Rut
When we think of AI as one particular thing, we drag the whole field down...

Self-driving Car Visualization and Gas Model
More self-driving car modeling. Now with a sweet animation of the steering! We start work on the gas model, converting to categorical variables, but predicting "always drive forward" is too good for the model to overcome...

Want to use your Python skills to break into Data Science?

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3 Reasons Counting is the Hardest Thing in Data Science
Counting is hard. You might be surprised to hear me say that, but it's true. As a data scientist, I've done it all - everything from simple regression analysis all the way to coding Hadoop MapReduce jobs that process hundreds of billions of data points each month. And, with all that experience, I've found that counting often involves far more time and effort...

Five great charts in 5 lines of R code each
Sharon Machlis is a journalist with Computerworld, and to show other journalists how great R is for data visualization she shows them these five data visualizations, each of which can be created in 5 lines of R code or less...

The Trouble with Chernoff
In 1973, applied statistician Herman Chernoff proposed one of the most strange and ingenious ideas in the history of information visualization – symbolizing data using faces...

The Data of Space
Lost. In. Spaaaaaaace! Cosmology! Astrophysics! Astronauts! This week we talk with some amazing guests!...

Can you get to know a person through data alone?
That’s the challenge two designers set themselves with a year-long exchange of hand-drawn infographics...

An Introduction to Contextual Bandits
In this post I discuss the Multi Armed Bandit problem and its applications to feed personalization. First, I will use a simple synthetic example to visualize arm selection in with bandit algorithms, I also evaluate the performance of some of the best known algorithms on a dataset for musical genre recommendations...

Full Resolution Image Compression with Recurrent Neural Networks
This paper presents a set of full-resolution lossy image compression methods based on neural networks. Each of the architectures we describe can provide variable compression rates during deployment without requiring retraining of the network: each network need only be trained once...

7 Ways To Be Driven Off A Data Cliff
You can proudly tell all your friends that you are leading a modern data-driven team. Nothing can go wrong, right? Incorrect. If you don’t pay attention, data can drive you off a cliff. This article discusses seven of the ways this can happen. Read on to ensure it doesn’t happen to you...

Data Scientist - Indeed - Austin, TX
As a Data Scientist at Indeed your role is to follow the data. Analyze, visualize, and model job search related data. You will build and implement machine learning models to make timely decisions. You will have access to unparalleled resources within Indeed to grow and develop both personally and professionally. We are looking for a mixture between a statistician, scientist, machine learning expert and engineer: someone who has passion for building and improving Internet-scale products informed by data. The ideal candidate understands human behavior and knows what to look for in the data...

TensorFlow in a Nutshell
The fast and easy guide to the most popular Deep Learning framework in the world...

An Intuitive Explanation of Convolutional Neural Networks
What are Convolutional Neural Networks and why are they important?...

How Convolutional Neural Networks Work
What’s especially cool about them is that they are easy to understand, at least when you break them down into their basic parts. I’ll walk you through it...

Machine Learning in Python: Essential Techniques for Predictive Analysis Machine Learning in Python shows you how to successfully analyze data using only two core machine learning algorithms, and how to apply them using Python...

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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