Artificial Intelligence, Machine Learning and Deep Learning

  • 4h
  • Oswald Campesato
  • Mercury Learning
  • 2020

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

About the Author

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).

In this Book

  • Introduction to AI
  • Introduction to Machine Learning
  • Classifiers in Machine Learning
  • Deep Learning Introduction
  • Deep Learning—RNNs and LSTMs
  • NLP and Reinforcement Learning

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