Data Science Weekly Newsletter

Issue

174

March 23, 2017

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Editor's Picks

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A new “Mathematician’s Apology”
In the two and a half years (or so) since I left academia for industry, I’ve worked with a number of math majors and math PhDs outside of academia and talked to a number of current grad students who were considering going into industry. As a result, my perspective on the role of the math research community within the larger world has changed quite a bit from what it was in the early days of may academic career. In the post below, I explore this new perspective...

Algorithms Tour: How data science is woven into the fabric of Stitch Fix
At Stitch Fix, we’re transforming the way people find what they love. Our clients want the perfect clothes for their individual preferences—yet without the burden of search or having to keep up with current trends. Our merchandise is curated from the market and augmented with our own designs to fill in the gaps. It’s kept current and extremely vast and diverse—ensuring something for everyone. Rich data on both sides of this 'market' enables Stitch Fix to be a matchmaker, connecting clients with styles they love (and never would’ve found on their own). ...

The Golden Age of Data Science [podcast]
How did one boy’s stuffed yellow elephant permanently intertwine itself in history? What is a data scientist? Why is right now the golden age for data science? We take a crack at all three of these questions—the second two, with the help of Gregory Piatetsky-Shapiro and Ryan Henning...

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Machine Learning Invades The Real World On Internet Balloons
Alphabet’s wacky-sounding plan to deliver the internet to the world’s farthest-flung places via giant balloons—is even closer to reality than the company previously thought. It’s cool that these balloons may soon start broadcasting internet signals from the stratosphere. But the bigger deal here is that machine learning is moving beyond its digital origins into the real world...

Image Compression using K-means Clustering : Colour Quantization
This post is a simple yet illustrative application of K-means clustering technique. Using K-means clustering, we will perform quantization of colours present in the image which will further help in compressing the image...

Isochrones using the Google Maps Distance Matrix API
I wrote a Python module called isocronut that will calculate isochrones around an origin point...In order to generate isochrones such as these, I made use of the Google Maps API. If you've never used the Google Maps API before, well then, buddy, now's your chance...

DiscoGAN
Official PyTorch implementation of Learning to Discover Cross-Domain Relations with Generative Adversarial Networks...

Who is that Neural Network?
Pokémon has been an enormous success around the globe for more than 20 years. In this paper, I tackle the “Who’s that Pokémon?” challenge from a machine learning perspective. I propose a machine learning pre-processing and classification pipeline, using convolutional neural networks for classification of Pokémon sprites...

10 Data Storytelling Videos from Tapestry 2017
Below are the ten presentations from the one-day event that spurred rich conversations both in-person as well as on social media,...

Which GPU(s) to Get for Deep Learning:
My Experience and Advice for Using GPUs in Deep Learning - UPDATED
With a good, solid GPU, one can quickly iterate over deep learning networks, and run experiments in days instead of months, hours instead of days, minutes instead of hours. So making the right choice when it comes to buying a GPU is critical. So how do you select the GPU which is right for you? This blog post will delve into that question and will lend you advice which will help you to make choice that is right for you...

Deck.gl – Data Visualization
I tried installing Deck.gl, MapBox, implement some code, take a deep understand in GLSL. Tried to visualize VisaH1B static, Flight record, Taxi route. All datasets are available on Kaggle which under CC license. And now, it’s time to write blog for sharing my experiment...

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Senior Data Analyst - VSCO - Oakland, CA
VSCO is a leading creative platform with a monthly audience of over 45 million and growing.
We are looking for a Senior Data Analyst to build data at VSCO from the ground up. You will design our data model for user behavior and content impression, and will mine the data to find insights that will influence the product roadmap. Expect to get your hands dirty with Redshift, Spark, and data visualization tools under the guidance of our Director of Data Science...

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Tutorial: Neural Machine Translation
German/English translation model demo w/ TensorFlow...

Self-Organising Maps: An Introduction
If you want to learn about machine learning techniques, the internet has you covered. In this post I want to talk about a less prevalent algorithm, but one that I like and that can be useful for different purposes. It’s called a Self-Organising Map (SOM)...

The world's simplest facial recognition api for Python and the command line
Recognize and manipulate faces from Python or from the command line with the world's simplest face recognition library. Built using dlib's state-of-the-art face recognition built with deep learning. The model has an accuracy of 99.38% on the Labeled Faces in the Wild benchmark...

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Data Smart: Using Data Science to Transform Information into Insight
"The best single book on Data Science today. I handle the data analysis and BI for the delivery side of a huge internet-based retail company, and have been a fan of Foreman's since his "Analytics Made Skeezy" blog days. His explanations are clear, his examples are to the point, and throughout it all, he is results-oriented."...

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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