Artificial Intelligence, Machine Learning, and Deep Learning

by Oswald Campesato

Overview

This book begins with an introduction to AI, followed by machine learning, deep learning, NLP, and reinforcement learning. Readers will learn about machine learning classifiers such as logistic regression, k-NN, decision trees, random forests, and SVMs. Next, the book covers deep learning architectures such as CNNs, RNNs, LSTMs, and auto encoders. Keras-based code samples are included to supplement the theoretical discussion. In addition, this book contains appendices for Keras, TensorFlow 2, and Pandas.

Features:

• Covers an introduction to programming concepts related to AI, machine learning, and deep learning
• Includes material on Keras, TensorFlow2 and Pandas

Product Details

ISBN-13:	9781683924678
Publisher:	Mercury Learning and Information
Publication date:	02/13/2020
Pages:	300
Product dimensions:	6.90(w) x 8.90(h) x 0.80(d)

About the Author

Campesato Oswald :

Oswald Campesato (San Francisco, CA) is an adjunct instructor at UC-Santa Clara and specializes in Deep Learning, Java, Android, TensorFlow, and NLP. He is the author/co-author of over twenty-five books including TensorFlow 2 Pocket Primer, Python 3 for Machine Learning, and the NLP Using R Pocket Primer (all Mercury Learning and Information).

Table of Contents

1: Introduction to AI
2: Introduction to Machine Learning
3: Classifiers in Machine Learning
4: Deep Learning Introduction
5: Deep Learning: RNNs and LSTMs
6: NLP and Reinforcement Learning
Appendices
A: Introduction to Keras
B: Introduction to TF2
C: Introduction to Pandas
Index