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MERCURY LEARNING and INFORMATION provides print and digital content in the areas of science and medicine, technology and computing, engineering, and mathematics (STEM disciplines) designed for the professional/reference, trade, library, higher education, career school, and online training markets. We embrace both traditional and innovative publishing models designed to accommodate the needs of the intended audience by using the appropriate delivery methods.

Artificial Intelligence, Machine Learning and Deep Learning Book CoverArtificial Intelligence, Machine Learning and Deep Learning

Oswald Campesato

ISBN: 9781683924678
Pub Date:  February 2020
Specs: 7 x 9   Paperback
Pages: 300
Price: $59.95


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 separate appendices for Keras, TensorFlow 2, and Pandas.



1: Introduction to AI. 2: Introduction to Machine Learning. 3: Machine Learning Classifiers. 4: Deep Learning and CNNs. 5: Deep Learning: RNNs and LSTMs. 6: Introduction to NLP and RL. Appendices. A: Introduction to Keras. B: Introduction to TF2. C: Working with Pandas.


Oswald Campesato (San Francisco, CA) specializes in Deep Learning, Java, Android, and TensorFlow. He is the author/co-author of over twenty-five books including Android Pocket Primer, Angular Pocket Primer, and the Python Pocket Primer (Mercury Learning).