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Data Science Weekly Newsletter
September 6, 2018

Editor's Picks

A Message From This Week's Sponsor

  • Mode Studio: SQL, Python, R, & charts in one platform
    No more jumping between applications. Mode Studio is the analytics toolkit that brings everything together, and gets out of the way. Explore data in our SQL editor, and pass results to integrated Python or R notebooks for deeper exploration and visualization. You can also layer charts over results quickly with built-in visualization tools, and sharing is easy—just send the report URL to teammates when you're ready...

Data Science Articles & Videos

  • Putting the Power of Kafka into the Hands of Data Scientists
    Over a year ago, my fellow data infrastructure engineers and I broke ground on a total rewrite of our event delivery infrastructure. Our mission was to build a robust, centralized data integration platform tailored to the needs of our Data Scientists. The platform would be fully self-service, so as to maximize the Data Scientists’ autonomy and give them complete control over their event data. Ultimately, we delivered a platform that is revolutionizing the way Data Scientists interact with Stitch Fix’s data...
  • Adversarial Examples that Fool Computer Vision and Time-Limited Humans
    Machine learning models are vulnerable to adversarial examples: small changes to images can cause computer vision models to make mistakes such as identifying a school bus as an ostrich. However, it is still an open question whether humans are prone to similar mistakes. Here, we address this question by leveraging recent techniques that transfer adversarial examples from computer vision models with known parameters and architecture to other models with unknown parameters and architecture, and by matching the initial processing of the human visual system. We find that adversarial examples that strongly transfer across computer vision models influence the classifications made by time-limited human observers...
  • Data Science and Robots
    If you want to understand the inner workings of machine learning and deep learning models, there is a very robust set of posts and videos here by Brandon Rohrer who according to his twitter profile "coaxes answers out of big piles of numbers for Facebook, builds robot brains for fun"...
  • Making it easier to discover datasets
    There are many thousands of data repositories on the web, providing access to millions of datasets; and local and national governments around the world publish their data as well. To enable easy access to this data, we [Google] launched Dataset Search, so that scientists, data journalists, data geeks, or anyone else can find the data required for their work and their stories, or simply to satisfy their intellectual curiosity....
  • A neural attention model for speech command recognition
    Attention models are powerful tools to improve performance on natural language, image captioning and speech tasks. The proposed model establishes a new stateof-the-art accuracy of 94.1% on Google Speech Commands dataset V1 and 94.5% on V2 (for the 20-commands recognition task), while still keeping a small footprint of only 202K trainable parameters...


  • Data Scientist - Dataminr - NYC
    We are Dataminr, the leading company that turns social media into real-time, actionable alerts. Our ability to find and deliver information faster than any traditional source has completely revolutionized how critical, relevant and actionable information reaches the news, finance, public sector and corporate security industries.
    You're a dedicated Data Scientist who wants nothing more than to help us sort, analyze and deliver relevant information from terabytes of unstructured data in the social media space. You will build machine learning models to transform social media feeds into actionable items. You will also work with engineers, product managers and other teams to solve challenging problems with your data science skills...

Training & Resources


  • Bayes Theorem: A Visual Introduction For Beginners
    "This book takes what can be a daunting and complex subject and breaks it down with a series of easy to follow examples which buildup to deliver a great overall explanation of how to use Bayes Theorem for basic analysis and even off-the-cuff critical thinking"...

    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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