Book Image

Deep Learning with TensorFlow

By : Giancarlo Zaccone, Md. Rezaul Karim, Ahmed Menshawy
Book Image

Deep Learning with TensorFlow

By: Giancarlo Zaccone, Md. Rezaul Karim, Ahmed Menshawy

Overview of this book

Deep learning is the step that comes after machine learning, and has more advanced implementations. Machine learning is not just for academics anymore, but is becoming a mainstream practice through wide adoption, and deep learning has taken the front seat. As a data scientist, if you want to explore data abstraction layers, this book will be your guide. This book shows how this can be exploited in the real world with complex raw data using TensorFlow 1.x. Throughout the book, you’ll learn how to implement deep learning algorithms for machine learning systems and integrate them into your product offerings, including search, image recognition, and language processing. Additionally, you’ll learn how to analyze and improve the performance of deep learning models. This can be done by comparing algorithms against benchmarks, along with machine intelligence, to learn from the information and determine ideal behaviors within a specific context. After finishing the book, you will be familiar with machine learning techniques, in particular the use of TensorFlow for deep learning, and will be ready to apply your knowledge to research or commercial projects.
Table of Contents (11 chapters)

Advanced TensorFlow Programming

Development of deep learning networks, especially when testing new models, may require rapid prototyping. For this reason, there have been developed several TensorFlow-based libraries, abstracting many programming concepts and providing higher-level building blocks.

In this chapter, we'll give an overview of the libraries such as, Keras, Pretty Tensor, and TFLearn.

For each library, we'll describe its main characteristics, with an application example.

The chapter is organized as follows:

  • Introducing Keras
  • Building deep learning models
  • Sentiment classification of movie reviews
  • Adding a convolutional layer
  • Pretty Tensor
  • Digit classifier
  • TFLearn
  • Titanic survival predictor