Learn Python and key libraries for TensorFlow with practical examples. Perfect for developers looking to enhance their skills.

Key Features

Introduction to Python basics

Hands-on code samples

Practical exercises

Book Description

As part of the best-selling Pocket Primer series, this book prepares programmers for machine learning and deep learning with TensorFlow. It begins with a quick introduction to Python, followed by chapters on NumPy, Pandas, Matplotlib, and scikit-learn. The final chapters provide TensorFlow 1.x code samples, including detailed examples for TensorFlow Dataset, crucial for TensorFlow 2. The journey starts with Python basics and progresses through essential data manipulation and visualization libraries. You’ll explore machine learning fundamentals with scikit-learn before diving into TensorFlow, learning to construct data pipelines with TensorFlow Dataset APIs like map(), filter(), and batch(). Understanding these concepts is vital for modern AI applications. This book transitions readers from basic programming to advanced machine learning and deep learning techniques, blending theory with practical skills. Companion files with source code enhance learning, making this an essential resource for mastering Python, machine learning, and TensorFlow.

What you will learn

Master Python essentials

Work with NumPy

Utilize Pandas

Create visualizations

Explore TensorFlow

Handle datasets

Who this book is for

Ideal for software developers with some programming experience. Readers should be familiar with basic command line operations. Prerequisites include a desire to learn TensorFlow and the motivation to follow through with exercises and code samples.