• Linear Programming and Healthy Diets
  My dad’s an interesting guy. Every so often he picks up a health trend and/or weight loss goal that would make many people’s jaw drop. He’s tried the “high fat” and “no fat” diets, and quite a few others. He’s concerned with losing weight, but also living longer, so he’s into caloric restriction among other things. Recently he asked me to help him optimize his diet...

• What is the yearly risk of another Harvey-level flood in Houston?
  You’ve likely heard that the flooding in Houston following Hurricane Harvey is reportedly a 500-year or even 1000-year flood event. You’ve perhaps also heard that this is the third 500-year flood that Houston has experienced in a three-year span, which calls into serious question the usefulness or accuracy of the “500-year flood” designation. This made me wonder: what’s our actual best estimate of the yearly risk for a Harvey-level flood, according to the data? That is the question I will attempt to answer here...

• The Language Of Hip-Hop: The Words Rapper Use (And Don't Use)
  Last year, data scientist Iain Barr determined the most “metal” words using an elegant methodology and machine learning. We were blown away and eagerly waited for someone to replicate it for other genres. One year later, we were still waiting. To start, we need a dataset that represents hip hop. We decided to use 26 million words from the lyrics of the top 500 charting artists on Billboard’s Rap Chart (about 50,000 songs)...

 
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• When Websites Design Themselves
  Today, we’re on the verge of another revolution, as artificial intelligence and machine learning turn the graphic design field on its head again. The vision is, to quote one project’s slogan, “websites that just make themselves.”...

• New Theory Cracks Open the Black Box of Deep Learning
  A new idea called the “information bottleneck” is helping to explain the puzzling success of today’s artificial-intelligence algorithms — and might also explain how human brains learn...

• Thoughts on higher-level visualization libraries & the visualization industry
  This weekend, I attended some of vizfest (d3.unconf). Like most conferences, I had opinions at times I didn’t feel extroverted enough to raise my hand. One of those cases was the discussion of higher-level visualization libraries. Treat this post as a hastily-written braindump of my thoughts...

• Apache Arrow and the "10 Things I Hate About pandas"
  In this post I hope to explain as concisely as I can some of the key problems with pandas's internals and how I've been steadily planning and building pragmatic, working solutions for them. To the outside eye, the projects I've invested in may seem only tangentially-related: e.g. pandas, Badger, Ibis, Arrow, Feather, Parquet. Quite the contrary, they are all closely-interrelated components of a continuous arc of work I started almost 10 years ago...

• The traveling metallurgist
  Explore simulated annealing & the traveling salesman problem: new interactive dataviz & blog post...

• PixelNN: Example-based Image Synthesis
  We present a simple nearest-neighbor (NN) approach that synthesizes high-frequency photorealistic images from an "incomplete" signal such as a low-resolution image, a surface normal map, or edges...

• Chiron: Translating nanopore raw signal directly into nucleotide sequence using deep learning
  Sequencing by translocating DNA fragments through an array of nanopores is a rapidly maturing technology which offers faster and cheaper sequencing than other approaches. However, accurately deciphering the DNA sequence from the noisy and complex electrical signal is challenging. Here, we report the first deep learning model - Chiron - that can directly translate the raw signal to DNA sequence without the error-prone segmentation step...

• How You Can Use the New Stack Overflow Bot from Microsoft
  So when Microsoft showed us how they were bringing AI to every developer through their platforms and tools, and asked if they could partner with us to create an AI driven experience for developers to use and learn with, we of course said yes...

• Neural Network from Scratch
  I've recently written an article on creating a simple neural network from scratch (perceptron linear classifier) in Python...

• Scalable Machine Learning (Part 2): Partial Fit
  This is part two of my series on scalable machine learning...

• NVIDIA Deep Learning Accelerator (NVDLA)
  The NVIDIA Deep Learning Accelerator (NVDLA) is a free and open architecture that promotes a standard way to design deep learning inference accelerators. With its modular architecture, NVDLA is scalable, highly configurable, and designed to simplify integration and portability. The hardware supports a wide range of IoT devices. Delivered as an open source project under the NVIDIA Open NVDLA License, all of the software, hardware, and documentation will be available on GitHub. Contributions are welcome...

• Reproducible Research with R and R Studio
  "a very practical book that teaches good practice in organizing reproducible data analysis and comes with a series of examples..."...
  For a detailed list of books covering Data Science, Machine Learning, AI and associated programming languages check out our resources page...