Mastering Machine Learning with scikit-learn, Second Edition Год издания: 2017 Автор: Gavin Hackeling Издательство: Packt Publishing Ltd. ISBN: 9781788299879 Язык: Английский Формат: PDF Качество: Издательский макет или текст (eBook) Интерактивное оглавление: Да Количество страниц: 254 Исходники: GitHub Описание:
Machine learning is the buzzword bringing computer science and statistics together to build smart and efficient models. Using powerful algorithms and techniques offered by machine learning you can automate any analytical model. This book examines a variety of machine learning models including popular machine learning algorithms such as k-nearest neighbors, logistic regression, naive Bayes, k-means, decision trees, and artificial neural networks. It discusses data preprocessing, hyperparameter optimization, and ensemble methods. You will build systems that classify documents, recognize images, detect ads, and more. You will learn to use scikit-learn’s API to extract features from categorical variables, text and images; evaluate model performance, and develop an intuition for how to improve your model’s performance. By the end of this book, you will master all required concepts of scikit-learn to build efficient models at work to carry out advanced tasks with the practical approach.
[ 2018-08-03 13:20 ]
Gavin Hackeling - Mastering Machine Learning with scikit-learn, Second Edition [2017, PDF, ENG] скачать торрент бесплатно и без регистрации
You cannot post new topics in this forum You cannot reply to topics in this forum You cannot edit your posts in this forum You cannot delete your posts in this forum You cannot vote in polls in this forum You cannot attach files in this forum You can download files in this forum
The site does not give electronic versions of products, and is engaged only in a collecting and cataloguing of the references sent and published at a forum by our readers. If you are the legal owner of any submitted material and do not wish that the reference to it was in our catalogue, contact us and we shall immediately remove her. Files for an exchange on tracker are given by users of a site, and the administration does not bear the responsibility for their maintenance. The request to not fill in the files protected by copyrights, and also files of the illegal maintenance!