Python machine learning programming ［PyTorch&scikit-learn edition］ impress top gear Tankobon Softcover – December 15, 2022
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Python machine learning programming ［PyTorch&scikit-learn edition］ impress top gear Tankobon Softcover – December 15, 2022
This book is irreplaceable, both as an overview of the ambitious field of machine learning and as a treasure trove of practical knowledge.
Python machine learning programming ［PyTorch&scikit-learn edition］ impress top gear Tankobon Softcover – December 15, 2022
Artikulli #: 87943410

Python machine learning programming ［PyTorch&scikit-learn edition］ impress top gear Tankobon Softcover – December 15, 2022

Artikulli #: 87943410

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This book is irreplaceable, both as an overview of the ambitious field of machine learning and as a treasure trove of practical knowledge.
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What Stands Out

Comprehensive Learning
Offers in-depth coverage of Python machine learning techniques, including practical applications with PyTorch and scikit-learn, catering to both beginners and advanced learners.
Hands-On Approach
Includes numerous coding examples and projects that enhance understanding and encourage practical application of machine learning concepts in real-world scenarios.
Updated Content
Published in December 2022, providing the latest insights and developments in machine learning technologies, ensuring readers are equipped with current and relevant knowledge.

Detajet e produktit

Shop Python machine learning programming ［PyTorch&scikit-learn edition］ impress top gear Tankobon Softcover – December 15, 2022 online at a best price in Albania. 429501558X
Item Weight1 lbs (450 grams)

Who Should Buy?

Suitable For
  • Beginner Data Scientists

    Ideal for newcomers wishing to grasp machine learning concepts using Python libraries like PyTorch and scikit-learn.

  • Students and Learners

    Perfect for academic use, excellent for students needing a comprehensive guide for projects and coursework in machine learning.

  • Professionals Upskilling

    Beneficial for professionals seeking to enhance their skills in Python programming and machine learning techniques.

Not Suitable For
  • Advanced Practitioners

    Not suitable for experts who require in-depth analysis or advanced techniques beyond the foundational concepts covered.

  • Complete Beginners

    Users with no programming experience may struggle without initial basic knowledge of Python or coding practices.

  • Casual Readers

    Individuals seeking a light read or casual information may find this technical book too dense and challenging.

PËRSHKRIMI I PRODUKTIT

Python machine learning programming ［PyTorch&scikit-learn edition］ impress top gear Tankobon Softcover – December 15, 2022

Keni ndonjë pyetje? Bisedoni me ne

Pyetje-përgjigjet për klientin

  • Pyetje: What programming languages does this book cover?

    Përgjigje: This book focuses on Python programming, specifically using libraries like scikit-learn and PyTorch.
  • Pyetje: Is this book suitable for beginners?

    Përgjigje: Yes, it starts with the basics of machine learning, making it accessible for beginners.
  • Pyetje: Does the book include practical coding examples?

    Përgjigje: Absolutely, the book includes practical coding examples to help implement the concepts learned.

Sebastian Raschka , uxi (Hayden) Liu , Vahid Mirjalili Editorial Review

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Pro

  • Comprehensive learning materials
  • User-friendly interface
  • Strong community support
  • Hands-on practical exercises
  • Covers popular libraries

Kundër

  • Some advanced topics may be brief.

Product Price History

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ALL 4471

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Karakteristikat dhe Përfitimet

  • Comprehensive guide covering basics to advanced machine learning techniques.
  • In-depth explanations of scikit-learn and PyTorch for practical applications.
  • Explores cutting-edge methods like Transformers and graph neural networks.
  • Features hyperparameter tuning, ensemble learning, and regression analysis.
  • Includes practical coding examples for real-world applications.
  • Highly recommended by readers and industry experts for effective learning.