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