Artificial Intelligence, Machine Learning, and Deep Learning

Artificial Intelligence, Machine Learning, and Deep Learning

Oswald Campesato
Paperback
February 2020
9781683924678
More details
  • Publisher
    Mercury Learning & Information
  • Published
    13th February
  • ISBN 9781683924678
  • Language English
  • Pages 300 pp.
  • Size 7" x 9"
$59.95
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January 2020
9781683924654
More details
  • Publisher
    Mercury Learning & Information
  • Published
    23rd January
  • ISBN 9781683924654
  • Language English
  • Pages 300 pp.
  • Size 7" x 9"
$179.95
E-Book
January 2020
9781683924661
More details
  • Publisher
    Mercury Learning & Information
  • Published
    23rd January
  • ISBN 9781683924661
  • Language English
  • Pages 300 pp.
  • Size 7" x 9"
$41.95
Add to Cart

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) specializes in Deep Learning, Data Cleaning, Java, Android, and TensorFlow. He is the author/co-author of over twenty-five books including TensorFlow Pocket Primer; Artificial Intelligence, Machine Learning, and Deep Learning; Android Pocket Primer, Angular4 Pocket Primer, and the Python Pocket Primer (Mercury Learning).

computer science