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Machine Learning by Design: Patterns and Principles for Data Collection, Feature Engineering, and Model Development
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Machine Learning by Design: Patterns and Principles for Data Collection, Feature Engineering, and Model Development
This 562-page guide is your companion through the entire ML workflow from data to models.
Machine Learning by Design: Patterns and Principles for Data Collection, Feature Engineering, and Model Development
商品＃: 91400209

Machine Learning by Design: Patterns and Principles for Data Collection, Feature Engineering, and Model Development

商品＃: 91400209

TWD 1825

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This 562-page guide is your companion through the entire ML workflow from data to models.
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What Stands Out

Comprehensive Framework
Delivers a structured approach to machine learning, enabling practitioners to effectively gather data, engineer features, and develop models, enhancing their project success rates.
Practical Insights
Offers actionable insights and best practices derived from real-world applications, ensuring users can overcome common challenges faced in machine learning projects.
User-Centric Design
Focuses on design principles that prioritize user needs, making it easier for data scientists and teams to apply concepts directly to their unique situations.

產品詳情

Shop Machine Learning by Design: Patterns and Principles for Data Collection, Feature Engineering, and Model Development online at a best price in Taiwan. B0DJSWJGY1
Publisher Independently published
Publication date October 9, 2024
Language English
Print length 562 pages
ISBN-13 979-8342441940
Item Weight 2.56 pounds (1.16 kg)
Dimensions 6.93 x 1.27 x 9.84 inches (17.6 x 3.2 x 25 cm)

產品描述

Machine Learning by Design: Patterns and Principles for Data Collection, Feature Engineering, and Model Development

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客戶問題與解答

  • 問題: Who is the author of this book?

    Answer: The author is Peng Shao, a former Staff ML Engineer at Twitter and a founding member of Alexa.
  • 問題: What does this guide cover?

    Answer: It covers the entire ML workflow from data collection to model development and includes best practices.
  • 問題: Is this book suitable for beginners?

    Answer: Yes, it provides foundational principles and guidance that can benefit both beginners and experienced practitioners.

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  • User-friendly design
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特色和優勢

  • Comprehensive 562-page guide on machine learning workflows.
  • Covers data collection, feature engineering, and model development.
  • Includes 15 timeless principles of machine learning with real-world examples.
  • Provides strategies for assembling high-quality datasets.
  • Step-by-step guidance for rapid model development and prototyping.
  • Best practices for model troubleshooting and tuning with technical details.

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