AI Publishing LLC, 2021. — 339 p. — ISBN 978-1-7347901-5-3. Python for Data Scientists — Scikit-Learn Specialization Scikit-Learn, also known as Sklearn, is a free, open-source machine learning (ML) library used for the Python language. In February 2010, this library was first made public. And in less than three years, it became one of the most popular machine learning...
New York: Packt Publishing, 2017. — 368 p. — ISBN13: 978-1787286382. Learn to use scikit-learn operations and functions for Machine Learning and deep learning applications. About This Book • Handle a variety of machine learning tasks effortlessly by leveraging the power of scikit-learn • Perform supervised and unsupervised learning with ease, and evaluate the performance of...
Packt Publishing, 2017. — 530 p. — ISBN: 978-1788833479. Use Python and scikit-learn to create intelligent applications Discover how to apply algorithms in a variety of situations to tackle common and not-so common challenges in the machine learning domain A practical, example-based guide to help you gain expertise in implementing and evaluating machine learning systems using...
2nd ed. — Packt Publishing, 2017. — 254 p. — ISBN: 978-1788299879. Key Features Master popular machine learning models including k-nearest neighbors, random forests, logistic regression, k-means, naive Bayes, and artificial neural networks Learn how to build and evaluate performance of efficient models using scikit-learn Practical guide to master your basics and learn from real...
Jamba Academy, 2023. — 423 p. — ISBN-13: 978-1960833044. Are you ready to dive into the world of Python Machine Learning? Look no further! "Python Machine Learning: A Beginner's Guide to Scikit-Learn" is the perfect guide for you. Written by experienced data scientist, Rajender Kumar, this book takes you on a journey through the basics of Machine Learning and the powerful...
Apress, 2019. — 208 p. — ISBN13: (electronic): 978-1-4842-5373-1. Aspiring data science professionals can learn the Scikit-Learn library along with the fundamentals of machine learning with this book. The book combines the Anaconda Python distribution with the popular Scikit-Learn library to demonstrate a wide range of supervised and unsupervised machine learning algorithms....
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