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157976159
Designing Machine Learning Systems: An Iterative Process for Production-Ready Applications Paper Cover – May 3, 2024
Item #:
157976159
AUD 77
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This is simply the best book you can read about how to develop, deploy, scale machine learning models in a company for the greatest impact.
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What Stands Out
Iterative Process
Emphasizes an iterative approach to machine learning system design, ensuring continuous improvement and adaptation, which leads to more refined and production-ready applications.
Practical Focus
Offers practical insights and methodologies that bridge the gap between theory and real-world application, making it invaluable for practitioners aiming to implement machine learning successfully.
Comprehensive Guidance
Provides comprehensive guidance on all phases of machine learning systems development, including planning, execution, and deployment, ensuring a well-rounded understanding for optimal results.
Product Details
| Publishers | Iceberg Publishing House |
| Date of publicization | May 3, 2024 |
| Prints | . |
| Language | Turkish |
| Print length | 416 pages |
| ISBN-10 | 6259855230 |
| ISBN-13 | 978-6259855233 |
| Dimensions | 20.8 x 1.8 x 13.8 cm |
Who Should Buy?
-
Data Scientists
Ideal for data scientists looking to enhance their skills in creating production-ready machine learning systems iteratively.
-
Machine Learning Engineers
Beneficial for ML engineers needing a structured approach to deploy machine learning applications efficiently and effectively.
-
AI Researchers
Useful for AI researchers focused on practical implementations and iterative processes in real-world machine learning applications.
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Beginners
Not suitable for beginners lacking foundational knowledge in machine learning concepts and systems.
Product Description
Designing Machine Learning Systems: An Iterative Process for Production-Ready Applications Paper Cover – May 3, 2024
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Customer Questions & Answers
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Question:
What is the main focus of the book?
Answer: The book focuses on designing reliable, scalable, and adaptable machine learning systems. -
Question:
Who is the author of the book?
Answer: The author is Chip Huyen, co-founder of Claypot AI. -
Question:
What benefits does this book offer to machine learning practitioners?
Answer: The book provides a framework for making informed design decisions, automating model processes, and ensuring responsible AI development.
Chip Huyen , Özgür Kaya (Çevirmen) Editorial Review
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Pros
- Good foundational knowledge
- Clear, structured approach
- Useful real-world examples
- Engaging writing style
- Covers essential concepts
Cons
- Some sections may lack depth.
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Features & Benefits
- Learn a holistic approach to designing reliable machine learning systems.
- Make informed design decisions through real case studies.
- Automate the continuous development and updating of models.
- Develop effective monitoring systems for production problems.
- Create a flexible machine learning platform adaptable to various scenarios.
- Build responsible and sustainable machine learning systems.
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