Start Machine Learning with Python ―Learn Feature Engineering and Machine Learning Basics with scikit-learn Tankobon Softcover – May 25, 2017
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Start Machine Learning with Python ―Learn Feature Engineering and Machine Learning Basics with scikit-learn Tankobon Softcover – May 25, 2017
Start your journey into machine learning with step-by-step instructions from an expert on the classic scikit-learn library.
Start Machine Learning with Python ―Learn Feature Engineering and Machine Learning Basics with scikit-learn Tankobon Softcover – May 25, 2017
товар №: 87921355

Start Machine Learning with Python ―Learn Feature Engineering and Machine Learning Basics with scikit-learn Tankobon Softcover – May 25, 2017

товар №: 87921355

€ 32

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What Stands Out

Beginner-Friendly Approach
This book offers a clear and concise introduction for beginners, making complex concepts in machine learning accessible and easy to understand with practical examples using Python and scikit-learn.
Focus on Feature Engineering
Emphasizing feature engineering, the book provides essential techniques and strategies, equipping readers with skills to enhance model performance and tackle real-world data challenges effectively.
Hands-On Learning
With practical exercises and real-world projects, readers can apply their knowledge immediately, reinforcing learning and boosting confidence in applying machine learning techniques in various scenarios.

Информация о продукте

Shop Start Machine Learning with Python ―Learn Feature Engineering and Machine Learning Basics with scikit-learn Tankobon Softcover – May 25, 2017 online at a best price in Estonia. 4873117984
Publisher u30aau30e9u30a4u30eau30fcu30b8u30e3u30d1u30f3
Publication date May 25, 2017
Edition First Edition
Language Japanese
Print length 373 pages
ISBN-10 4873117984
ISBN-13 978-4873117980
Item Weight 680 g
Dimensions 9.45 x 7.48 x 0.98 inches (24 x 19 x 2.5 cm)

Who Should Buy?

Suitable For
  • Beginner Programmers

    Ideal for those new to programming who want to grasp machine learning fundamentals using Python.

  • Data Enthusiasts

    Perfect for individuals interested in exploring data science and machine learning applications through hands-on experience.

  • Self-learners

    Great for independent learners seeking structured material for understanding feature engineering and scikit-learn.

Not Suitable For
  • Advanced Users

    Not suitable for experienced practitioners already familiar with machine learning concepts and scikit-learn.

  • Academic Researchers

    May not meet the advanced theoretical knowledge demands typical of academic research in machine learning.

  • Busy Professionals

    Not ideal for individuals with limited time who require concise, high-level machine learning over detailed tutorials.

ОПИСАНИЕ ТОВАРА

Start Machine Learning with Python ―Learn Feature Engineering and Machine Learning Basics with scikit-learn Tankobon Softcover – May 25, 2017

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Вопросы и ответы клиентов

  • вопрос: Who is the author of this book?

    отвечать: The author is a seasoned expert and release manager for scikit-learn.
  • вопрос: What topics are covered in this book?

    отвечать: The book covers machine learning basics, feature engineering, and model evaluation.
  • вопрос: Is this book suitable for beginners?

    отвечать: Yes, it provides a solid foundation for individuals starting their machine learning journey.

Andreas C. Muller , Sarah Guido , 中田秀基 & 0 Electricity & Communications Editorial Review

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€ 32

Закажите сейчас и получите товар приблизительно Суббота, Июль 11

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Ubuy works hard to protect your security and privacy. Our advanced payment security system ensures confidentiality by encrypting your information during transmission using AES (Advanced Encryption Standards) and SSL (Secure Socket Layer) protocols. Your payment details are 100% secure as we do not share your payment details with third party sellers.

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Особенности и преимущества

  • Expert guidance from a seasoned scikit-learn release manager.
  • Step-by-step instructions for mastering machine learning basics.
  • In-depth coverage of feature engineering and model evaluation.
  • Build highly accurate predictive models with practical techniques.
  • Unique features not found in conventional machine learning manuals.
  • Perfect for beginners looking to establish a solid foundation.