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Machine Learning Refined: Foundations, Algorithms, and Applications
89% of respondents would recommend this to a friend
DZD 13338
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With its intuitive yet rigorous approach to machine learning, this text provides students with the fundamental knowledge and practical tools needed to conduct research and build data-driven products.
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What Stands Out
Product Details
| Publisher | Cambridge University Press |
| Publication date | 9 Jan. 2020 |
| Edition | 2nd |
| Language | English |
| Print length | 594 pages |
| ISBN-10 | 1108480721 |
| ISBN-13 | 978-1108480727 |
| Item weight | 1.36 kg |
| Dimensions | 17.15 x 3.18 x 24.77 cm |
Who Should Buy?
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Data Scientists
Ideal for professionals seeking a comprehensive understanding of machine learning concepts, algorithms, and practical applications.
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Students
Perfect for university students in computer science or data science programs wanting foundational knowledge in machine learning.
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Industry Professionals
Beneficial for business analysts or engineers looking to implement machine learning solutions in real-world scenarios.
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Beginners
Not suitable for those with no background in programming or data science, as it may be overwhelming.
Product Description
Machine Learning Refined: Foundations, Algorithms, and Applications
Customer Questions & Answers
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Question:
What type of examples are included in the book?
Answer: Examples are included from disciplines including computer vision, natural language processing, economics, neuroscience, recommender systems, physics, and biology. -
Question:
What online resources are provided?
Answer: A suite of online resources including sample code, data sets, interactive lecture slides, and a solutions manual are provided online. -
Question:
Who is the target audience for this book?
Answer: This book is ideal for graduate courses on machine learning and for individual reference and self-study.
Higher Education Editorial Review
Machine Learning Refined Foundations, Algorithms, And Applications offers a comprehensive 2nd edition published by Cambridge University Press. With 594 pages of in-depth exploration, it delves into various machine learning algorithms and their practical applications. The book is well-structured, making complex concepts accessible to readers. It is printed in English and has received positive feedback for its clarity and thoroughness, making it an essential resource for both students and professionals interested in the field of machine learning.
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Pros
- Comprehensive coverage of algorithms and applications
- Well-structured and easy to understand
- Suitable for both students and professionals
- Thorough exploration of machine learning concepts
- High-quality publication from a reputable publisher
Cons
- Some readers may find it quite dense to read.
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DZD 13338
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Features & Benefits
- Intuitive and rigorous approach to machine learning
- Includes essential mathematical prerequisites
- Practical applications emphasized
- Over 300 color illustrations for technical concepts
- Over 100 in-depth coding exercises in python
- Ideal for graduate courses and individual self-study
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