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An Introduction to Statistical Learning: with Applications in Python (Springer Texts in Statistics)
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An Introduction to Statistical Learning: with Applications in Python (Springer Texts in Statistics)
An Introduction to Statistical Learning: with Applications in Python (Springer Texts in Statistics)
Nº de artículo: 74381285

An Introduction to Statistical Learning: with Applications in Python (Springer Texts in Statistics)

90% of respondents would recommend this to a friend

Nº de artículo: 74381285

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What Stands Out

Practical Applications
Focuses on real-world applications of statistical learning using Python, making it accessible for practitioners and students alike.
Comprehensive Coverage
Covers a vast range of statistical methods and machine learning techniques, providing a thorough foundation for learners at all levels.
User-Friendly Approach
Designed with clarity in mind, featuring detailed explanations and examples that simplify complex concepts for easier comprehension.

Detalles de producto

Publisher Springer
Publication date July 1, 2023
Edition 2023rd
Language English
Print length 622 pages
ISBN-10 3031387465
ISBN-13 978-3031387463
Item Weight 3.6 pounds (1.63 kg)
Dimensions 7.17 x 1.65 x 10.08 inches (18.2 x 4.2 x 25.6 cm)
Part of series Springer Texts in Statistics

Who Should Buy?

Suitable For
  • Beginner Students

    Ideal for students new to statistical learning and looking for clear explanations and practical applications using Python.

  • Data Scientists

    Useful for data scientists seeking to enhance their statistical analysis skills with hands-on Python projects and exercises.

  • Educators

    Great resource for instructors who want a comprehensive textbook for teaching statistical learning methodologies in Python.

Not Suitable For
  • Advanced Statisticians

    May not meet the needs of advanced statisticians looking for in-depth theoretical insights beyond practical applications.

DESCRIPCIÓN DEL PRODUCTO

An Introduction to Statistical Learning: with Applications in Python (Springer Texts in Statistics)

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Probability & Statistics Editorial Review

An Introduction to Statistical Learning: with Applications in Python (Springer Texts in Statistics) offers a robust framework for understanding machine learning fundamentals. Published by Springer in July 2023, this edition introduces essential updates such as new chapters on Neural Networks, making it relevant for current practices. As noted in reviews, the book effectively explains concepts with clear examples and visualizations, providing a self-contained resource ideal for graduate courses or personal enrichment. However, users have raised concerns about the binding of the paperback edition, indicating that pages may come loose with heavy use. Overall, it serves as an excellent reference for those looking to strengthen their grasp on statistics within machine learning contexts.

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ventajas

  • New chapters reflect current trends in machine learning.
  • Clear explanations and well-structured examples.
  • Visualizations are easy to read and understand.
  • Self-contained resource with comprehensive coverage.
  • Highly recommended for graduate-level courses.

Contras

  • Binding of the paperback edition can be problematic.

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