Machine Learning With Pytorch And Scikit-learn Develop Machine Learning And Deep - Sebastian Raschka

₩105,690
+ ₩60,449 배송

Machine Learning With Pytorch And Scikit-learn Develop Machine Learning And Deep - Sebastian Raschka

  • 브랜드: Unbranded
판매자::

Machine Learning With Pytorch And Scikit-learn Develop Machine Learning And Deep - Sebastian Raschka

  • 브랜드: Unbranded

₩105,690

재고 있음
+ ₩60,449 배송

14일 반품 정책

판매자::

₩105,690

재고 있음
+ ₩60,449 배송

14일 반품 정책

결제 방법:

설명

Machine Learning With Pytorch And Scikit-learn Develop Machine Learning And Deep - Sebastian Raschka

This Book Of The Bestselling And Widely Acclaimed Python Machine Learning Series Is A Comprehensive Guide To Machine And Deep Learning Using Pytorch S Simple To Code Framework.purchase Of The Print Or Kindle Book Includes A book book In book Format.key Features:- Learn Applied Machine Learning With A Solid Foundation In Theory- Clear, Intuitive Explanations Take You Deep Into The Theory And Practice Of Python Machine Learning- Fully Updated And Expanded To Cover Pytorch, Transformers, Xgboost, Graph Neural Networks, And Best Practicesbook Description:machine Learning With Pytorch And Scikit-learn Is A Comprehensive Guide To Machine Learning And Deep Learning With Pytorch. It Acts As Both A Step-by-step Tutorial And A Reference You'll Keep Coming Back To As You Build Your Machine Learning Systems.packed With Clear Explanations, Visualizations, And Examples, The Book Covers All The Essential Machine Learning Techniques In Depth. While Some Books Teach You Only To Follow Instructions, With This Machine Learning Book, We Teach The Principles Allowing You To Build Models And Applications For Yourself.why Pytorch?pytorch Is The Pythonic Way To Learn Machine Learning, Making It Easier To Learn And Simpler To Code With.
  • 브랜드: Unbranded
  • 카테고리: Computing & Internet
  • 출판사/레이블: Packt Publishing
  • 페이지 수: 774
  • 형식: Paperback
  • 언어: English
  • 저자: Sebastian Raschka
  • Fruugo ID: 435231089-912882806
  • ISBN: 9781801819312

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  • STANDARD: ₩60,449 - 배달 사이 수 29 7월 2026–화 04 8월 2026

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