Artificial Intelligence, Machine Learning, and Deep Learning
- Publisher
Mercury Learning and Information - Published
13th February 2020 - ISBN 9781683924678
- Language English
- Pages 300 pp.
- Size 7" x 9"
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- Publisher
Mercury Learning and Information - Published
23rd January 2020 - ISBN 9781683924654
- Language English
- Pages 300 pp.
- Size 7" x 9"
- Publisher
Mercury Learning and Information - Published
23rd January 2020 - ISBN 9781683924661
- Language English
- Pages 300 pp.
- Size 7" x 9"
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
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
Oswald Campesato
Oswald Campesato (San Francisco, CA) is an adjunct instructor at UC-Santa Clara and specializes in Deep Learning, Java, Android, and TensorFlow. He is the author/co-author of over twenty-five books including TensorFlow 2 Pocket Primer, Python 3 for Machine Learning, and the Python Pocket Primer (Mercury Learning).