Introduction To Statistical Learning Python
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13 juillet 2025
Springer International Publishing AG
An Introduction to Statistical Learning: With Applications in Python
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Springer
An Introduction to Statistical Learning: with Applications in R
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This book presents some of the most important modeling and prediction techniques, along with relevant applications
Topics include linear regression, classification, re-sampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, and more. Color graphics and real-world examples are used to illustrate the methods presented.
Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform
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Springer
An Introduction to Statistical Learning: with Applications in Python
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93
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Springer
Statistical Learning with Math and Python: 100 Exercises for Building Logic
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Introduction to Statistical Learning: A Comprehensive Guide to R Programming, Data Visualization, Linear Regression, Decision Tree, Clustering, Dimensionality Reduction and Many More (English Edition)
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Technics Publications
Machine Learning and Data Science: An Introduction to Statistical Learning Methods with R
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Independently published
Artificial Intelligence with R and Python for Beginners:: An Introduction to Statistical Analysis and Machine Learning
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Chapman & Hall/CRC
An Introduction to R and Python for Data Analysis: A Side-By-Side Approach
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Springer
A First Course in Statistical Learning: With Data Examples and Python Code (Statistics and Computing) (English Edition)
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Packt Publishing
The Statistics and Calculus with Python Workshop: A comprehensive introduction to mathematics in Python for artificial intelligence applications
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#10
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