Tensorflow Solutions for Data [Video]

More Information
  • Create data to predict loan performance
  • Build a RESTful API to make predictions on table data
  • Create a machine learning model for sentence generation
  • Build a system to generate realistic data

In this video you'll work with categorical data to predict loan performance. Categorical, structured data often appears in spreadsheets and relational databases, common data sources in business. This technique can be used to effectively predict performance or detect potential fraud.

You will also work with recurrent neural networks, which generate realistic test and placeholder data. This is useful to fill in systems with synthetic test data to simulate load and test the breadth of a working system andpredict one column from the others.

Style and Approach

This course takes a step-by-step approach, helping you explore all the functioning of TensorFlow.

  • Master the different deep learning paradigms and build a real-world project to predict loan performance with table data
  • Create a self-learning model for data generation
  • Your handy guide 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 30 minutes
ISBN 9781788475488
Date Of Publication 19 Jan 2018


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/