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Data Science Weekly Newsletter
February 7, 2019

Editor's Picks

  • Android Accessibility: Live Transcribe
    Imagine a world where people who are deaf or hard of hearing can have everyday in-person conversations, in real time. Google research scientist Dimitri Kanvesky and engineer Chet Gnegy worked together to bring Live Transcribe, a new Android app, to life to accomplish just that...
  • CB Insights: Here are the top 100 AI companies in the world
    Fortunately, the folks at CB Insights have taken the bull by the horns. They today published their third annual cohort of AI startups — a compilation of 100 of the most promising companies (whittled down from a pool of over 3,000) providing hardware and data infrastructure for AI apps, optimizing machine learning workflows, and applying AI across a range of industries. The selections were based on factors including — but not limited to — patent activity, investor profile, market potential, partnerships, competitive landscape, team strength, and novelty...

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Data Science Articles & Videos

  • Generalized Language Models
    As a follow up of word embedding post, we will discuss the models on learning contextualized word vectors, as well as the new trend in large unsupervised pre-trained language models which have achieved amazing SOTA results on a variety of language tasks...
  • AlphaStar: An Evolutionary Computation Perspective
    In January 2019, DeepMind revealed AlphaStar to the world-the first artificial intelligence (AI) system to beat a professional player at the game of StarCraft II-representing a milestone in the progress of AI. AlphaStar draws on many areas of AI research, including deep learning, reinforcement learning, game theory, and evolutionary computation (EC). In this paper we analyze AlphaStar primarily through the lens of EC, presenting a new look at the system and relating it to many concepts in the field...
  • Analyzing & Improving Representations with the Soft Nearest Neighbor Loss
    We explore and expand the Soft Nearest Neighbor Loss to measure the entanglement of class manifolds in representation space: i.e., how close pairs of points from the same class are relative to pairs of points from different classes. We demonstrate several use cases of the loss. As an analytical tool, it provides insights into the evolution of class similarity structures during learning. Surprisingly, we find that maximizing the entanglement of representations of different classes in the hidden layers is beneficial for discrimination in the final layer...
  • Why Is It so Hard to Put Data Science in Production?
    At Blue Yonder, our team has more than eight years of experience delivering and operating data science applications for retail customers. In that time, we have learned some painful lessons — including how hard it is to bring data science applications into production...
  • The Data Scientist Profile In 2019
    Last year we conducted a research into 1,001 data scientist profiles, which had great success all around the online data science community. This year we have recreated the research with new data and have posted it on our blog. We’ve not only included the contemporary findings, but also comparisons with last year’s research...


  • Data Scientist - TRANZACT - Fort Lee, 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 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...
        Want to post a job here? Email us for details >>

Training & Resources

  • Multi-label Text Classification using BERT – The Mighty Transformer
    In this article, we will focus on application of BERT to the problem of multi-label text classification. Traditional classification task assumes that each document is assigned to one and only on class i.e. label. This is sometimes termed as multi-class classification or sometimes if the number of classes are 2, binary classification...
  • Linear Algebra for Deep Learning [Lecture]
    Getting the notational conventions right to find a sweet spot between mathematical LinAlg notation and how we actually implement it in DL frameworks to make the transition from lecture to HW smoother for students was actually quite tricky...


  • The Book of R: A First Course in Programming and Statistics
    "The Book of R is a comprehensive, beginner-friendly guide to R, the world’s most popular programming language for statistical analysis. Even if you have no programming experience and little more than a grounding in the basics of mathematics, you’ll find everything you need to begin using R effectively for statistical analysis"...

    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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