Machine Learning with Python
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Tarkeshwar Barua
About this book
This book explains how to use the programming language Python to develop machine learning and deep learning tasks. It provides readers with a solid foundation in the fundamentals of machine learning algorithms and techniques. The book covers a wide range of topics, including data preprocessing, supervised and unsupervised learning, model evaluation, and deployment. By leveraging the power of Python, readers will gain the practical skills necessary to build and deploy effective machine learning models, making this book an invaluable resource for anyone interested in exploring the exciting world of artificial intelligence.
- From the basics to the advanced applications, with examples from the real world.
- "Hands-on" and questions sections for each chapter.
Author / Editor information
Tarkeshwar Barua, Blue Crest Univ., Liberia; Kamal Kant Hiran, Sir Padampat Singhania University, India; Ritesh Kumar Jain, Geetanjali Inst. of Tech. Studies, India; Doshi Ruchi, Universidad Azteca, Mexico
Topics
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Frontmatter
I -
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Contents
V -
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Chapter 1 Introduction to Machine Learning
1 -
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Chapter 2 Basics of Python Programming
30 -
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Chapter 3 Data Preprocessing in Python
90 -
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Chapter 4 Foundations of Machine Learning
152 -
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Chapter 5 Classic Machine Learning Algorithms
188 -
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Chapter 6 Advanced Machine Learning Techniques
316 -
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Chapter 7 Neural Networks and Deep Learning
360 -
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Chapter 8 Specialized Applications and Case Studies
424 -
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References
471 -
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Index
475
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Manufacturer information:
Walter de Gruyter GmbH
Genthiner Straße 13
10785 Berlin
productsafety@degruyterbrill.com
