Table of Contents

Introduction

Chapter 1: A General Overview of Deep Learning

Artificial Intelligence, Machine Learning, and Deep Learning

Modeling of Machine Learning

Foreseeable Benefits of Deep Learning

Chapter 2: The Arithmetic Foundations of a Neural Network

A Peek into a Neural Network

Data Attributes of Neural Networks

Gearing the Neural Network through Tensor Operations

Gradient-Based Optimization in Neural Networks

Chapter 3: Starting Our Tasks with Neural Networks

Inspection of a Neural Network

What is Keras?

The Pre-requisites for a Deep Learning Workstation

Deep Learning Binary Classification Example

Deep Learning Multiclass Classification Example

Deep Learning Regression Example

Chapter 4: Using Deep Learning for Computer Vision

What is Convnet? Working with Convolution Operations

Training a Convnet

Working with a Pretrained Convnet

Chapter 5: Mastering Advanced Practices in Deep Learning

Keras Functional API

Inspection of Deep Learning Models Using Keras Callbacks and Tensorboards

Tensorboard: The TensorFlow Visualization Network

Working with Advanced Methods and Getting Optimized Results

Conclusion