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Data Science Weekly Newsletter
Issue
86
July 16, 2015

## A Message From This Week's Sponsor

• Want to be a Data Scientist, but don't know where to start?
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## Data Science Articles & Videos

• Can deep learning help find the perfect girl?
When a Machine Learning PhD student at University of Montreal starts using Tinder, he soon realises that something is missing in the dating app - the ability to predict to which girls he is attracted. Harm de Vries applies Deep Learning to assist in the pursuit of the perfect match...
• Searching for Approximate Nearest Neighbours
Nearest neighbour search is a common task: given a query object represented as a point in some (often high-dimensional) space, we want to find other objects in that space that lie close to it. For example, a mapping application will perform a nearest neighbours search when we ask it for restaurants close to our location. Nearest neighbour search underpins two crucial systems at Lyst...
• “Don’t Invert That Matrix” – Why And How
The first time I read John Cook’s advice “Don’t invert that matrix,” I wasn’t sure how to follow it. I was familiar with manipulating matrices analytically (with pencil and paper) for statistical derivations, but not with implementation details in software...We’ll chug through a computation example below, to illustrate the difference between these two methods. But first, let’s start with some context: a common statistical situation where you may think you need matrix inversion, even though you really don’t...
• Learning from the experience of others with mixed effects models
At Stitch Fix we have many problems that boil down to finding the best match between items in two sets. Our recommendation algorithms match inventory to clients with the help of the expert human judgment of our stylists. We also match these stylists to clients. This blog post is about the remarkably useful application of some classical statistical models to these and similar problems that feature repeated measurements...
• The Definitive Guide to Do Data Science for Good
You are a fully-equipped (or aspiring) data scientist and want to use your precious skills for solving problems that really itch the world? Welcome to the club. The good news is that there are many ways for data scientists to do good. However, the path is not always beaten and you might need to show some initiative. This article will give you some insight on how you can get involved, either through group meetings and events, as a volunteer or in paid positions...

## Jobs

• Project Development Lead - Bayes Impact - San Francisco, CA Bayes Impact is a YC-backed technology nonprofit that uses data science to solve pressing social challenges across the globe. We build intuitive and powerful software applications that empower governments, nonprofits, and individuals to make critical, data-driven decisions. We turn data into actions that impact the lives of billions of people. We are a small team of open-minded, driven, egalitarian, usually sarcastic people who think there’s more to life than ad targeting algorithms and whatever messaging app kids will use next week. We are looking for talented, big-hearted individuals who are hungry for hard problems that uplift people in need...

## Training & Resources

• Learn Data Science the Hard Way
So you want to be a Data Scientist? The good news is that there are tons of great resources out there to learn from. The bad? None is comprehensive, and choosing the best can be completely overwhelming. I created this list to help you stay focused on learning what’s important, the easiest way possible. But it won’t be easy...
• mpl colormaps
Viridis, the new, perceptually-accurate color map for matplotlib...

## Books

• Automate the Boring Stuff with Python:
Practical Programming for Total Beginners
Recent release recommended by a couple of our readers...
"Introductions to python are easy to find -- but at the end of the day most python tutorials for beginners end up being the same lessons repackaged, often leaving the new programmer with gaping holes in how their newly acquire skills can be applied practically. This is not one of those books..."... 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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