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Data Science Weekly Newsletter
September 27, 2018

Editor's Picks

  • Forecasting at Uber: An Introduction
    This article is the first in a series dedicated to explaining how Uber leverages forecasting to build better products and services. In recent years, machine learning, deep learning, and probabilistic programming have shown great promise in generating accurate forecasts. In addition to standard statistical algorithms, Uber builds forecasting solutions using these three techniques. Below, we discuss the critical components of forecasting we use, popular methodologies, backtesting, and prediction intervals...
  • The Coming Revolution In Software Development
    Amid the deep learning hype, though, many observers miss the biggest reason to be optimistic about its future: deep learning requires coders to write very little actual code. Rather than relying on preset rules or if-then statements, a deep learning system writes rules automatically based on past examples. A software developer only has to create a “rough skeleton,” to paraphrase Andrej Karpathy from Tesla, then let the computers do the rest...

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Data Science Articles & Videos

  • Artificial Intelligence Has a Strange New Muse: Our Sense of Smell
    Scientists trying to gain a better understanding of how organisms process chemical information have uncovered coding strategies that seem especially relevant to problems in AI. Moreover, olfactory circuits bear striking similarities to more complex brain regions that have been of interest in the quest to build better machines....
  • The Future is Tiny
    Break down of the changes that are happening in the embedded world. Key point is that tiny general-purpose computers are replacing every other kind of hardware controller...
  • Deep Learning with Electronic Health Record (EHR) Systems
    Walk down the aisle at any machine learning conference and ask people about the applications of ML in healthcare and most will respond with the canonical example of using computer vision to diagnose diseases from medical scans (followed by a prolonged debate about “should radiologists be worried about their jobs”). But there exists another source of data, beyond medical scans, that can change the way we approach health: the electronic health record (EHR)...


  • Data Scientist - Pear Therapeutics - San Francisco or Boston

    At Pear Therapeutics, we have the privilege of building the world’s first-ever class of prescription digital therapeutics. By nature of our therapeutics as digital applications, we have access to rich datasets and unique opportunities to drive clinical outcomes. As a Data Scientist, you will be responsible for shaping and delivering data-driven insights. We are looking for data scientists with a deep product sense, who have an innate curiosity, and are eager to dive into large, complex datasets and create actionable insights....

Training & Resources

  • 6 Steps To Write Any Machine Learning Algorithm From Scratch: Perceptron Case Study
    Writing a machine learning algorithm from scratch is an extremely rewarding learning experience. It provides you with that "ah ha!" moment where it finally clicks, and you understand what’s really going on under the hood. In this article I’ll walk you through a 6-step process to write algorithms from scratch, using the Perceptron as a case-study...


  • Data Visualization with Python and JavaScript:
    Scrape, Clean, Explore & Transform Your Data
    Learn how to turn raw data into rich, interactive web visualizations with the powerful combination of Python and JavaScript. With this hands-on guide, author Kyran Dale teaches you how build a basic dataviz toolchain with best-of-breed Python and JavaScript libraries—including Scrapy, Matplotlib, Pandas, Flask, and D3—for crafting engaging, browser-based visualizations...

    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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