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lgli/Matt Harrison - Machine Learning Les fondamentaux (2020, First Interactive).epub
Machine Learning Les fondamentaux - collection O'Reilly 🔍
HARRISON, Matt First interactive ; O'Reilly, Paris, France, [Sebastopol, Californie, 2020
法语 [fr] · 英语 [en] · EPUB · 2.5MB · 2020 · 📘 非小说类图书 · 🚀/lgli/zlib · Save
描述
EDEN3086862
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zlib/no-category/Matt Harrison/Machine Learning Les fondamentaux_21280075.epub
备选标题
Машинное обучение: карманный справочник: краткое руководство по методам структурированного машинного обучения на Python
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Machine learning : les fondamentaux - Exploiter des données structurées en Python (French Edition)
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Machine Learning Pocket Reference : Working with Structured Data in 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
Matt Harrison, 1975-
备选作者
Харрисон, Мэтт
备用出版商
Dorling Kindersley Publishers Ltd
备用出版商
O'Reilly Media, Incorporated
备用出版商
Диалектика; Диалектика
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Editions First Livres
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Ladybird Books Ltd
备用出版商
edi8
备用版本
First edition, Beijing ; Boston ; Farnham ; Sebastopol ; Tokyo, 2019
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United Kingdom and Ireland, United Kingdom
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First edition, North Sebastopol, CA, 2019
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United States, United States of America
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Москва, Санкт-Петербург, Russia, 2020
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O'Reilly Media, Sebastopol, 2019
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France, France
备用版本
1, 2019-09-17
备用版本
1, PS, 2019
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 datasetCleaning data and dealing with missing dataExploratory data analysisCommon preprocessing steps using sample dataSelecting features useful to the modelModel selectionMetrics and classification evaluationRegression examples using k-nearest neighbor, decision trees, boosting, and moreMetrics for regression evaluationClusteringDimensionality reductionScikit-learn pipelines
备用描述
Entrez de plain-pied dans le monde fascinant la data science avec cet ouvrage pratique, véritable pense bête de tous les data scientists, ingénieurs ou programmeurs Vous aussi participez à la révolution qui ramène l'intelligence artificielle au coeur de notre société, grace aux data scientists. La data science consiste à traduire des problèmes de toute autre nature, en problèmes de modélisation quantitative, résolus par des algorithmes de traitement. Au programme : Les différentes versions de Python L'apprentissage non supervisé et le préprocessing Représenter les données Processus de validation Algorithmes, chaînes et pipeline Travailler avec des données de type texte Utiliser Sikit-learn.
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
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
2022-04-08
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