Data Science Weekly - Issue 165
Issue #165 Jan 19 2017
Editor Picks
A short history of color theory
Although a basic understanding of the color spectrum is rather easy to develop, color theory is an almost infinitely complex subject with roots in both science and art. It can therefore be a daunting task to learn about color composition in a way that is true to both art history and scientific truth...
Engineering is the bottleneck in (Deep Learning) research
I just had to write up a little rant ;)...
AI Pioneer Wants to Build the Renaissance Machine of the Future
Juergen Schmidhuber, often referred to as the father of AI, raised venture capital for his startup looking to teach machines to solve any problem...
A Message from this week's Sponsor: DataScience.com
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Data Science Articles & Videos
You Draw It: What Got Better or Worse During Obama’s Presidency
Draw your guesses on the charts below to see if you’re as smart as you think you are... [with the code behind it here]
Mathematical Model Reveals the Patterns of How Innovations Arise
The work could lead to a new approach to the study of what is possible, and how it follows from what already exists....
Watch an AI supercomputer battle top pros in a $200,000 poker tournament
It knows when to hold ‘em, and when to fold ‘em...
Scraping for Craft Beers
If you have read some of my posts in the past, you know by now that I enjoy a good craft beer. I decided to mix business with pleasure and write a tutorial about how to scrape a craft beer dataset from a website in Python...
Recognizing Traffic Lights With Deep Learning
How I learned deep learning in 10 weeks and won $5,000...
The More You Know: Using Knowledge Graphs for Image Classification
Humans have the remarkable capability to learn a large variety of visual concepts, often with very few examples, whereas current state-of-the-art vision algorithms require hundreds or thousands of examples per category and struggle with ambiguity. One characteristic that sets humans apart is our ability to acquire knowledge about the world and reason using this knowledge. This paper investigates the use of structured prior knowledge in the form of knowledge graphs and shows that using this knowledge improves performance on image classification...
Unrolled Generative Adversarial Networks
This repo contains an example notebook with a TensorFlow implementation of unrolled GANs on a 2d mixture of Gaussians dataset...
Scaling Recommendation Engine: 15,000 to 130M Users in 24 Months
Delivering users with precise product recommendations (recs) is the creative force that drives Retention Science to continue to iterate, improve and innovate. In this post, our team unveils our iteration from a minimum viable product to a production-ready solution...
Jobs
Data Scientist & Machine Learning Researcher - American Express - NYC As a Data Scientist in the Machine Learning and Data Science Team, you will help American Express accelerate its digital transformation. You will be challenged with designing winning data products and developing new big data capabilities that will elevate American Express to the forefront of the digital revolution...
Training & Resources
Tutorial: Deep Learning in PyTorch
An Unofficial Startup Guide...
The Anatomy of Deep Learning Frameworks
In this post, I have tried to sketch out these common principles which would help you better understand the frameworks and for the brave hearts among you, provide a guide on how to implement your own deep learning framework...
Machine Learning for Artists
In general, this book will try to minimize the use of math, and rely on visual aides more than equations, both because neural networks can be well understood this way, and because it helps reduce the need for other qualifications...
Books
Algorithms for Data Science "This groundbreaking textbook on practical data analytics unites fundamental principles, algorithms, and data. Programming fluency and experience with real and challenging data sets are gained through more than 20 Python and R tutorials and lots of exercises with solutions."...
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