Book Image

Deep Learning Essentials

By : Wei Di, Jianing Wei, Anurag Bhardwaj
3 (1)
Book Image

Deep Learning Essentials

3 (1)
By: Wei Di, Jianing Wei, Anurag Bhardwaj

Overview of this book

Deep Learning a trending topic in the field of Artificial Intelligence today and can be considered to be an advanced form of machine learning. This book will help you take your first steps in training efficient deep learning models and applying them in various practical scenarios. You will model, train, and deploy different kinds of neural networks such as CNN, RNN, and will see some of their applications in real-world domains including computer vision, natural language processing, speech recognition, and so on. You will build practical projects such as chatbots, implement reinforcement learning to build smart games, and develop expert systems for image captioning and processing using Python library such as TensorFlow. This book also covers solutions for different problems you might come across while training models, such as noisy datasets, and small datasets. By the end of this book, you will have a firm understanding of the basics of deep learning and neural network modeling, along with their practical applications.
Table of Contents (12 chapters)

Recent models for deep learning

A number of recent deep learning techniques have been proposed that extend the core ideas of deep learning to new applications and learning scenarios. In this section, we will cover two such models that have gained prominence recently.

Generative Adversarial Networks

Recently, one popular field of machine learning that has seen the use of deep learning techniques is generative learning. Generative learning can be defined as a technique for learning joint probability estimates, P(x,y) from features and labels. It builds a probabilistic model of labels and can be robust to missing data and noisy data. Additionally, such models can also be used to generate samples, which can be further used to...