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)

TensorFlow and Keras

In this section we are going to address a very important feature for all data scientists and machine learning enthusiasts which is the integration of TensorFlow and Keras. Having this feature on board, you will be able to build a very complex deep learning systems with very few lines of code.

Figure 5: TensorFlow and Keras Integration (Source: https://blog.keras.io/img/keras-tensorflow-logo.jpg)

What is Keras?

Keras is an API that makes using and building deep learning models easier and faster. So it's a deep learning toolbox that's all about:

  • Ease of use
  • Reducing complexity
  • Reducing cognitive load

And by making deep learning easier to use what happens is that you are making it accessible to more people. So the key design concept...