Artificial Intelligence, Machine Learning, and Deep Learning:

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 architectu...

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Bibliographic Details
Main Author: Campesato, Oswald (Author)
Format: Electronic eBook
Language:English
Published: Herndon Mercury Learning and Information [2020]
Subjects:
Online Access:DE-1046
DE-1043
DE-858
DE-859
DE-860
DE-739
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Summary: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 learningIncludes material on Keras, TensorFlow2 and Pandas
Item Description:Description based on online resource; title from PDF title page (publisher's Web site, viewed 01. Nov 2023)
Physical Description:1 Online-Ressource (300 Seiten)
ISBN:9781683924654
DOI:10.1515/9781683924654

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