About This Book

Step into the amazing world of Artificial Intelligence and Machine Learning using this compact and easy to understand book. Dive into Neural Networks and Deep Learning and create your own production ready AI models by using TensorFlow and Keras.

Work through simple yet insightful examples that will get you up and running with Artificial Intelligence, TensorFlow and Keras in no time.

Who This Book Is For

This book is for Python developers who want to understand Neural Networks from ground up and build real-world Artificial Intelligence applications. This book is friendly to Python beginners, but being familiar with Python would be useful to play around with the code.

What You Will Learn

The basic structure and functionality of a Neuron

The basic math behind the Neural Network learning process

See how to build a simple character recognition model from ground up

What classification, regression and clustering is

How to use TensorFlow to build production ready models

Build a first model with the Keras framework

How to predict the survival chance for Titanic passengers

How to build a simple book recommender

How to detect toxic language with an AI model

In Detail

Artificial Intelligence became one of the hottest topics in the modern economy, where everything is driven by software, network and data. There exists nearly no startup nor traditional business where Artificial Intelligence is not used extensively across many fields such as search engines, image recognition, robotics or finance.

This book gives a ground up, step by step introduction about how a Neural Network is used to learn a given function and to make intelligent data-driven decisions.

The book explains how to identify typical use-cases such as classification, regression and clustering in terms of practical and well known use-cases.

This book comes with an introduction into the state-of-the-art Google TensorFlow framework that allows developers to roll out their models in production.

On top of TensorFlow, the Keras library is used to simplify the design and training of complex deep-learning models.

This book comes with multiple examples that show how to apply Artificial Intelligence and Machine Learning models for use-cases such as handwriting recognition, decision making, text analysis and toxic comment identification as well as the use of AI to recommend products to customers.