Machine training using Python. Collection of recipes
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The book contains about 200 recipes for solving practical tasks of machine learning, such as loading and processing text or numerical data, modeling, reducing dimension and many others. Work with Python and its libraries, including Pandas and Scikit-LEARN, has been considered. Solutions of all problems are accompanied by detailed explanations. Each recipe contains a working program code that can be inserted, combined and adapted, creating its own application.
Support recipes using: vectors, matrices and arrays, data processing, text, images, dates and time, reducing the dimension and methods of highlighting or selecting signs, evaluating and selecting models, linear and logistics regression, trees, forests and forests and forests, and K of the nearest neighbors, supporting vehicles (SVM), naive bayes classifiers, clustering and neural networks, preserving and loading trained models
Support recipes using: vectors, matrices and arrays, data processing, text, images, dates and time, reducing the dimension and methods of highlighting or selecting signs, evaluating and selecting models, linear and logistics regression, trees, forests and forests and forests, and K of the nearest neighbors, supporting vehicles (SVM), naive bayes classifiers, clustering and neural networks, preserving and loading trained models
Author:
Author:Elbon Chris
Cover:
Cover:Soft
Category:
- Category:Computer & Technology
ISBN:
ISBN:978-5-9775-4056-8
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