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
Vare #: 87943410

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

Vare #: 87943410

DKK 320

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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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Hvad der skiller sig ud

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.

Produktdetaljer

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

Hvem bør købe?

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.

PRODUKTBESKRIVELSE

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

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Kundespørgsmal & svar

  • spørgsmål: What programming languages does this book cover?

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

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

    svar: 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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Fordele

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

Ulemper

  • Some advanced topics may be brief.

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DKK 320

Bestil nu og få den omkring Torsdag, Juli 02

QTY:

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Hurtigste grænseoverskridende levering

Egenskaber og fordele

  • 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.