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Machine Learning And Deep Learning With Python eBook

by James Chen
language: english
Publisher: Distributed By Ingram Spark, June of 2023 ‧
79,49€
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This book is a comprehensive guide to understanding and implementing cutting-edge machine learning and deep learning techniques using Python programming language. Written with both beginners and experienced developers in mind, this book provides a thorough overview of the foundations of machine learning and deep learning, including mathematical fundamentals, optimization algorithms, and neural networks.

Starting with the basics of Python programming, this book gradually builds up to more advanced topics, such as artificial neural networks, convolutional neural networks, and generative adversarial networks. Each chapter is filled with clear explanations, practical examples, and step-by-step tutorials that allow readers to gain a deep understanding of the underlying principles of machine learning and deep learning.

Throughout the book, readers will also learn how to use popular Python libraries and packages, including numpy, pandas, scikit-learn, TensorFlow, and Keras, to build and train powerful machine learning and deep learning models for a variety of real-world applications, such as regression and classification, K-means, support vector machines, and recommender systems.

Whether you are a seasoned data scientist or a beginner looking to enter the world of machine learning, this book is the ultimate resource for mastering these cutting-edge technologies and taking your skills to the next level. High-school level of mathematical knowledge and all levels (including entry-level) of programming skills are good to start, all Python codes are available at Github.com.

Machine Learning And Deep Learning With Python

by James Chen

Property Description
ISBN: 9781738908424
Publisher: Distributed By Ingram Spark
Release Date: June of 2023
Language: English
Pages: 393
Format: eBook
File Format and Compatibility:
Categories: eBooks in English > Others
EAN: 9781738908424
Acessibilidade: Ver características de acessibilidade indicadas pelo editor