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
Sprache
Verlagsort
Zielgruppe
Für Beruf und Forschung
US School Grade: College Graduate Student
Dateigröße
ISBN-13
978-1-68392-465-4 (9781683924654)
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Schweitzer Klassifikation
