About this video

This course is all about some of the most exciting applications of Deep Learning and how to implement them in TensorFlow. You will learn how to build models to solve problems in different domains such as Computer vision, Natural Language Processing, Reinforcement Learning, Finance, and more.

Taking a Cookbook approach, this course presents you with easy-to-follow recipes to show the use of advanced Deep Learning techniques and their implementation in TensorFlow. After taking this tutorial you will be able to start building advanced Deep Learning models with TensorFlow for applications with a wide range of fields.

All the code and supporting files for this course are available on Github at https://github.com/PacktPublishing/-TensorFlow-1.X-Deep-Learning-Recipes-for-Artificial-Intelligence-Applications-v-

Style and Approach

The course takes a Cookbook approach and will show you how to build models to solve problems in different domains such as computer vision, natural language processing, Reinforcement Learning, Finance, and more.

Publication date:
June 2018
3 hours 5 minutes

About the Author

  • Alvaro Fuentes

    Alvaro Fuentes is a data scientist with more than 12 years of experience in analytical roles. He holds an M.S. in applied mathematics and an M.S. in quantitative economics. He worked for many years in the Central Bank of Guatemala as an economic analyst, building models for economic and financial data. He founded Quant Company to provide consulting and training services in data science topics and has been a consultant for many projects in fields such as business, education, medicine, and mass media, among others.

    He is a big Python fan and has been using it routinely for five years to analyze data, build models, produce reports, make predictions, and build interactive applications that transform data into intelligence.

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