#mlearning

Machine Learning Innovation Summit

Separate the Signal from the Noise

San Francisco, 2016

Why
Attend

The Machine Learning Innovation Summit offers unique insight and discussion on the benefits that you will see from investing in machine learning to drive business innovation.
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Our
Speakers

Hear from this year's stellar line up of influential data scientists. People thinking about the future of machine learning

  • Danny Lange

    Head of Machine Learning

    Uber
    Uber
  • Hamed Valizadegan

    Research Scientist

    NASA
    NASA
  • Todd Holloway

    Director, Algorithms

    Netflix
    Netflix
  • Inmar Givoni

    VP, Big Data

    Kobo
    Kobo
  • Nish Parikh

    Head of Data Science

    eBay
    eBay
  • Chul Lee

    Director, Data

    Under Armour
    Under Armour
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The
Schedule

As organizations evolve and embrace technological advances, data becomes a key currency on which they can hope to gain an advantage over competitors and push business success. Machine learning offers a new solution - the ability for algorithms to learn without the need to be programmed.

Our
Sponsors

Are you looking to showcase big data technologies or analytics initiatives in front of the most influential industry gathering of the year? If the answer is yes then visibility at the Summit is an absolute must.

Who
Attends

Check out the companies attending the event below.

The
Venue

Fairmont San Francisco

World-renowned, Fairmont San Francisco presents an awe-inspiring picture of historic San Francisco. The grandeur of the luxury hotel atop Nob Hill coupled with its reputation for impeccable service promises a truly memorable experience during your San Francisco vacation. Known for turning moments into memories for leisure and business travelers alike this luxury San Francisco hotel has been host to some of the most influential meetings and events, breathtaking weddings and personalized special occasions of the century.
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Executive Summary

Machine Learning Innovation Summit

June 8 & 9, San Francisco, 2016

Separate the Signal from the Noise
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