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...
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...
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...
Packt Publishing, 2020. — 399 p. — ISBN: 978-1838826048. Machine learning is applied everywhere, from business to research and academia, while scikit-learn is a versatile library that is popular among machine learning practitioners. This book serves as a practical guide for anyone looking to provide hands-on machine learning solutions with scikit-learn and Python toolkits. The...
Packt Publishing, 2020. — 399 p. — ISBN: 978-1838826048. Machine learning is applied everywhere, from business to research and academia, while scikit-learn is a versatile library that is popular among machine learning practitioners. This book serves as a practical guide for anyone looking to provide hands-on machine learning solutions with scikit-learn and Python toolkits. The...
Packt Publishing Ltd., 2020. — 368 p. — ISBN: 978-1-83882-604-8. Code files only! Integrate scikit-learn with various tools such as NumPy, pandas, imbalanced-learn, and scikit-surprise and use it to solve real-world machine learning problems Machine learning is applied everywhere, from business to research and academia, while scikit-learn is a versatile library that is popular...
New York: Packt Publishing, 2017. — 368 p. About This Book Learn how to handle a variety of tasks with Scikit-Learn with interesting recipes that show you how the library really works Use Scikit-Learn to simplify the programming side data so you can focus on thinking Discover how to apply algorithms in a variety of situations Who This Book Is For If you're a data scientist...
New York: Packt Publishing, 2017. — 368 p. About This Book Learn how to handle a variety of tasks with Scikit-Learn with interesting recipes that show you how the library really works Use Scikit-Learn to simplify the programming side data so you can focus on thinking Discover how to apply algorithms in a variety of situations Who This Book Is For If you're a data scientist...
Packt Publishing, 2017. — 374 p. Learn to use scikit-learn operations and functions for Machine Learning and deep learning applications. Python is quickly becoming the go-to language for analysts and data scientists due to its simplicity and flexibility, and within the Python data space, scikit-learn is the unequivocal choice for machine learning. This book includes walk throughs...
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...
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...
Amazon Digital Services LLC, 2018. This book is a guide for you on how to use Scikit-Learn, a machine learning library for Python programming language. The author first helps you know what Scikit-Learn are and how to set it up on your system. You are also guided on how to load datasets into Scikit-Learn. The author has then guided you on how to use the various machine learning...
Packt Publishing, 2017. — 530 p. — ISBN: 978-1788833479. About This Book 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...
Packt Publishing, 2017. — 530 p. — ISBN: 978-1788833479. !Only code files About This Book 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...
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...
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...
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...
Packt Publishing, 2014. — 221 p. — ISBN: 978-1-78398-836-5. 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 life...
Packt Publishing, 2014. — 238 p.
This book examines machine learning models including logistic regression, decision trees, and support vector machines, and applies them to common problems such as categorizing documents and classifying images. It begins with the fundamentals of machine learning, introducing you to the supervised-unsupervised spectrum, the uses of training and...
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...
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...
Packt Publishing, 2014. — 214 p.
Python is quickly becoming the go-to language for analysts and data scientists due to its simplicity and flexibility, and within the Python data space, scikit-learn is the unequivocal choice for machine learning. Its consistent API and plethora of features help solve any machine learning problem it comes across.
The book starts by walking...
2nd ed. — Packt Publishing, 2017. — 368 p. — ISBN: 178728638X. True PDF Data Analysts already familiar with Python but not so much with scikit-learn, who want quick solutions to the common machine learning problems will find this book to be very useful. If you are a Python programmer who wants to take a dive into the world of machine learning in a practical manner, this book...
Packt Publishing, 2020. — 164 p. — ISBN: 978-1-78934-370-0. Deploy supervised and unsupervised machine learning algorithms using scikit-learn to perform classification, regression, and clustering. Scikit-learn is a robust machine learning library for the Python programming language. It provides a set of supervised and unsupervised learning algorithms. This book is the easiest...
Packt Publishing, 2020. — 164 p. — ISBN: 978-1-78934-370-0. Code files only! Deploy supervised and unsupervised machine learning algorithms using scikit-learn to perform classification, regression, and clustering. Scikit-learn is a robust machine learning library for the Python programming language. It provides a set of supervised and unsupervised learning algorithms. This book...
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...
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. — 246 p. — ISBN: 1484253728. 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. Care is taken to walk you...
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....
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....
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....
Методические рекомендации. — Воронеж : Воронежский институт МВД России, 2021. — 51 с. В методических рекомендациях приводится методика обработки данных экспертных оценок с использованием оригинальных алгоритмов на основе slice-матриц. Предназначены для слушателей факультета переподготовки и повышения квалификации, обучающихся по дополнительным профессиональным программам...
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