1 The amazing world of TensorFlow

1.1 What is TensorFlow?

1.1.1 An overview of popular components of TensorFlow

1.1.2 Using TensorFlow to build and deploy a machine learning model

1.2 GPU vs CPU

1.3 When and when not to use TensorFlow?

1.3.1 When to use TensorFlow?

Prototyping deep learning models

Implementing models (including non-deep learning) that can run faster on optimized hardware

Productionize models / Serving on cloud

Monitoring models during model training

Creating heavy-duty data pipelines

1.3.2 When not to use TensorFlow?

Implementing traditional machine learning models

Manipulating and analysing small-scale structured data

Creating complex natural language processing (NLP) pipelines

1.4 What will this book teach you?

1.4.1 TensorFlow fundamentals

1.4.2 Deep learning algorithms

1.4.3 Monitoring and optimization

1.5 Who is this book for?

1.6 Should we really care about Python and TensorFlow 2

1.7 Summary