Tensorflow Solutions for Text [Video]

More Information
Learn
  • Fetch data from an email
  • Use encoders to detect sample data
  • Use recommenders to predict word similarity
  • Predict output probabilities for data
  • Build an automatic email server
About

This volume introduces working with text, with a focus on the most plentiful source of text out there: email. Working with email text from your own Gmail account, you will build up a label predictor, similar in effect to the technology Google uses to power the Social and Promotions tabs. With this technique, you will be able to build your own email classification and automated workflow hooks.

Style and Approach

This course deals with the core topics in a highly practical manner with focus on code.

Features
  • Master various deep learning paradigms and build a real-world project using unstructured text
  • Your handy tutorial to mastering deep learning with Tensorflow with interesting use-cases to ensure a quality learning experience
  • Build practical, real-world deep-learning projects in Tensorflow
Course Length 1 hour 55 minutes
ISBN 9781788399180
Date Of Publication 13 Dec 2017

Authors

Will Ballard

Will Ballard is the chief technology officer at GLG, responsible for engineering and IT. He was also responsible for the design and operation of large data centers that helped run site services for customers including Gannett, Hearst Magazines, NFL, NPR, The Washington Post, and Whole Foods. He has also held leadership roles in software development at NetSolve (now Cisco), NetSpend, and Works (now Bank of America). https://www.linkedin.com/in/will-ballard-b09115/