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upload/newsarch_ebooks_2025_10/2019/09/20/Machine Learning Pocket Reference - Matt Harrison.epub
Machine Learning Pocket Reference : Working with Structured Data in Python 🔍
Harrison, Matt O'Reilly Media, Incorporated, O'Reilly Media, Sebastopol, 2019
英语 [en] · EPUB · 24.5MB · 2019 · 📘 非小说类图书 · 🚀/lgli/lgrs/upload · Save
描述
Introduction -- Overview of the machine learning process -- Classification walkthrough : titanic dataset -- Missing data -- Cleaning data -- Exploring -- Preprocess data -- Feature selection -- Imbalanced classes -- Classification -- Model selection -- Metrics and classification evaluation -- Explaining models -- Regression -- Metrics and regression evaluation -- Explaining regression models -- Dimensionality reduction -- Clustering -- Pipelines.
备用文件名
lgli/r:\!fiction\0day\1\Machine Learning Pocket Reference_ Working with Structured Data in Python - Matt Harrison (O'Reilly Media;2019;9781492047544;eng).epub
备用文件名
lgrsnf/r:\!fiction\0day\1\Machine Learning Pocket Reference_ Working with Structured Data in Python - Matt Harrison (O'Reilly Media;2019;9781492047544;eng).epub
备选标题
Машинное обучение: карманный справочник: краткое руководство по методам структурированного машинного обучения на Python
备选标题
Harrison, M: Machine Learning Pocket Reference
备选作者
Мэтт Харрисон; перевод с английского и редакция В. А. Коваленко
备选作者
Matthew Harrison
备选作者
Харрисон, Мэтт
备用出版商
Hamlyn Children's Books
备用出版商
Диалектика; Диалектика
备用出版商
Egmont Books Ltd
备用出版商
Dean & Son
备用版本
First edition, Beijing ; Boston ; Farnham ; Sebastopol ; Tokyo, 2019
备用版本
United Kingdom and Ireland, United Kingdom
备用版本
First edition, North Sebastopol, CA, 2019
备用版本
United States, United States of America
备用版本
Москва, Санкт-Петербург, Russia, 2020
备用版本
1st edition, Beijing, 2019
备用版本
1, 2019-09-17
备用版本
1, 20190827
备用版本
1, PS, 2019
元数据中的注释
lg2634355
元数据中的注释
Предм. указ.: с. 307-312
Пер.: Harrison, Matt Machine learning Beijing etc. : O'Reilly, cop. 2019 978-1-492-04754-4
元数据中的注释
РГБ
元数据中的注释
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备用描述
With detailed notes, tables, and examples, this handy reference will help you navigate the basics of structured machine learning. Author Matt Harrison delivers a valuable guide that you can use for additional support during training and as a convenient resource when you dive into your next machine learning project.
Ideal for programmers, data scientists, and AI engineers, this book includes an overview of the machine learning process and walks you through classification with structured data. You'll also learn methods for clustering, predicting a continuous value (regression), and reducing dimensionality, among other topics.
This pocket reference includes sections that cover:
Classification, using the Titanic dataset Cleaning data and dealing with missing data Exploratory data analysis Common preprocessing steps using sample data Selecting features useful to the model Model selection Metrics and classification evaluation Regression examples using k-nearest neighbor, decision trees, boosting, and more Metrics for regression evaluation Clustering Dimensionality reduction Scikit-learn pipelines
备用描述
With detailed notes, tables, and examples, this handy reference will help you navigate the basics of structured machine learning. Author Matt Harrison delivers a valuable guide that you can use for additional support during training and as a convenient resource when you dive into your next machine learning project. Ideal for programmers, data scientists, and AI engineers, this book includes an overview of the machine learning process and walks you through classification with structured data. You'll also learn methods for clustering, predicting a continuous value (regression), and reducing dimensionality, among other topics. -- Provided by publisher
备用描述
A Quick Guide to Structured Machine Learning Techniques
开源日期
2020-07-26
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