Data Science Weekly Newsletter - Issue 296

Issue #296

July 25 2019

Editor Picks
 
  • Machine Learning and Data Science Applications in Industry
    A curated list of applied machine learning and data science notebooks and libraries accross different industries. The code in this repository is in Python (primarily using jupyter notebooks) unless otherwise stated. The catalogue is inspired by awesome-machine-learning...
  • Facebook speeds up mapping data validation with Map With AI and RapiD
    Millions of roads around the world have yet to be mapped, and that’s a real problem, particularly in the developing world. Map With AI is designed to make adding and editing roads quick and relatively simple. It achieves this in part by leveraging a novel method of predicting road networks from commercially available satellite imagery from Maxar, which enables it to accommodate regional road differences...
  • How the Transformers broke NLP leaderboards
    A big reason why NLP is such an actively developed area is the leaderboards: they are the core of multiple shared tasks, benchmark systems like GLUE, and individual datasets such as SQUAD and AllenAI datasets. Leaderboards stimulate competitions between engineering teams, helping them to develop better and better models to tackle human language. Or do they?...
 
 

A Message from this week's Sponsor:

 

 
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Data Science Articles & Videos

 
  • Reverse Engineering the Big Mac™ Index
    My central hypothesis was that I could predict the price of a Big Mac using a country’s economic data. Extensive economic data is readily available from the World Bank and the BMI data is available from The Economist and other online sources. My challenge was to find the most predictive features, build a model to predict Big Mac prices, then benchmark the model on a held out test set...
  • How NerdWallet Dialed Machine Learning up to 11
    Over the past year I have been working on building out Nerdwallet’s Machine Learning platform which concerns itself with providing infrastructure and workflows that let data scientists easily build and deploy models to production! I wrote a blog post on our solution and I figured our approach was worth sharing out to the broader data science community...
  • Kitchen disruption: Better food through artificial intelligence
    Looking for that perfect recipe, or a new flavor combination that delights the senses? Increasingly, players in the food industry are embracing artificial intelligence to better understand the dynamics of flavor, aroma and other factors that go into making a food product a success...
  • Behind the Selection of the NeurIPS 2019 Workshops
    NeurIPS 2019 workshop decisions went out just moments ago! This guest post is brought to you by this year’s Workshop Chairs, Jenn Wortman Vaughan, Marzyeh Ghassemi, Shakir Mohamed, and Bob Williamson. We want to give you some highlights from the innovative proposals we saw and describe the process that we used for selection...
  • Deep Hough Voting for 3D Object Detection in Point Clouds
    In this work, we return to first principles to construct a 3D detection pipeline for point cloud data and as generic as possible. However, due to the sparse nature of the data -- samples from 2D manifolds in 3D space -- we face a major challenge when directly predicting bounding box parameters from scene points: a 3D object centroid can be far from any surface point thus hard to regress accurately in one step. To address the challenge, we propose VoteNet, an end-to-end 3D object detection network based on a synergy of deep point set networks and Hough voting...
  • GPS Routes Plotted on Realistic 3D Map
    Going into this project I had a vision of somehow plotting my cycling routes on a realistic 3D map. Previously, I had mapped my routes on a 2D map to create a heat map but I felt like something was missing. It occured to me that I had the elevation data for all of these routes and it seemed likely that open source elevation data was available. Eventually I came across the Rayshader package and was blown away; it was exactly what I was looking for to create the 3D map. This article will go through how to create your own 3D mapped route...
  • How to Become More Marketable as a Data Scientist
    Recently, jointly with my team, we analyzed 300 vacancies for data scientists to define skills most in-demand. Based on the results we obtained, we created a rating of the skills for data scientists in 2019...

 

Event*

 

 

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Data Leaders Summit Europe gathers Chief Data Officers, Chief Analytics Officers and Chief Data Scientists from Europe’s largest companies.

Download the agenda to find out exactly who is speaking, what are the hottest topics and how Data Leaders Summit can benefit you. Then, take a look at the https://bit.ly/2xGGPCD here to find out how you can get 15% off your ticket price with code DATALEADERSMP19

*Sponsored post. If you want to be featured here, or as our main sponsor, contact us!

 

Jobs

 
  • Senior Data Scientist - TRANZACT - NJ or Raleigh, NC

    Tranzact is a fast paced, entrepreneurial company offering a well-rounded suite of marketing solutions to help insurance companies stay ahead of the competition. The Senior Data Scientist will be solving the toughest problems at Tranzact by using data. More specifically, responsible for gathering data, conducting analysis, building predictive algorithms and communicating findings to drive profitable growth and performance across Tranzact. Must have a strong grasp on the data structure, business needs, and statistical and predictive modeling. Minimum 7 years of experience building predictive algorithms...

        Want to post a job here? Email us for details >> team@datascienceweekly.org
 

 

Training & Resources

  • Image segmentation
    This tutorial focuses on the task of image segmentation, using a modified U-Net...
  • Managing machines
    Pete Skomoroch covers what you need to know as we shift from a world of deterministic programs to systems that give unpredictable results on ever-changing training data...
 
 

Books

 

 
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For a detailed list of books covering Data Science, Machine Learning, AI and associated programming languages check out our resources page.

 
P.S., Enjoy the newsletter? Please forward it to your friends and colleagues - we'd love to have them onboard :) All the best, Hannah & Sebastian
 
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