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End-to-end Machine Learning with TensorFlow on Google Cloud Platform

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TensorFlow is an “end-to-end open source platform for machine learning”, with a “comprehensive, flexible ecosystem of tools, libraries and community resources that lets researchers push the state-of-the-art in ML and developers easily build and deploy ML-powered applications”. It was developed by the Google Brain team and open-sourced under the Apache 2 license in 2015. (ML, short for machine learning, is a subset of AI, artificial intelligence.)

Since then, it (TensorFlow) has become somewhat of an industry standard application for conducting machine learning tasks and research. And with the increasing adoption of machine learning techniques in most aspects of business and manufacturing, having some machine learning knowledge will serve you well in the job market. But how do you go about acquiring that knowledge?

According to Deloitte Global’s TMT predictions for 2019, “Among companies that adopt AI technology, 70 percent will obtain AI capabilities through cloud-based enterprise software, and 65 percent will create AI applications using cloud-based development services.”

That’s a hint, a strong one, on how to go about acquiring some machine learning skills. And that’s why the organizers of Big Data & AI Conference are offering the End-to-end Machine Learning with TensorFlow on Google Cloud Platform workshop during the Big Data & AI Conference, which will take place in Dallas, Texas, from June 27 – 29, 2019. The workshop itself is scheduled for Day 1 of the conference, that is, on June 27, 2019.

The workshop instructors will be Karl Weinmeister, the Cloud AI Advocacy Manager for Google, and Fatih Nar, a Customer Engineer for Google. For complete information on the workshop, including cost and links to registration, visit the End-to-end Machine Learning with TensorFlow on Google Cloud Platform workshop page.

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