Overview of TensorFlow and Machine Learning

TensorFlow is a popular library for implementing machine learning-based solutions. It includes a low-level API known as TensorFlow core and many high-level APIs, including two of the most popular ones, known as TensorFlow Estimators and Keras. In this chapter, we will learn about the basics of TensorFlow and build a machine learning model using logistic regression to classify handwritten digits as an example.

We will cover the following topics in this chapter:

• TensorFlow core:
  • Tensors in TensorFlow core
  • Constants
  • Placeholders
  • Operations
  • Tensors from Python objects
  • Variables
  • Tensors from library functions

• Computation graphs:
  • Lazy loading and execution order
  • Graphs on multiple devices – CPU and GPGPU
  • Working with multiple graphs
• Machine learning, classification, and logistic regression
• Logistic regression examples in TensorFlow
• Logistic regression examples in Keras