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:	9781683924661
Publisher:	Mercury Learning & Information
Publication date:	01/23/2020
Sold by:	Barnes & Noble
Format:	eBook
Pages:	300
File size:	4 MB

About the Author

Oswald Campesato (San Francisco, CA) is an adjunct instructor at UC-Santa Cruz and specializes in Deep Learning, NLP, Android, and Python. He is the author/co-author of over forty-five books including Data Science Fundamentals Pocket Primer, Python 3 for Machine Learning, and the Python Pocket Primer (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