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Machine Learning Refined: Foundations, Algorithms, and Applications
86% of respondents would recommend this to a friend
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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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O que se Destaca
Detalhes do produto
- 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. The authors prioritize geometric intuition and algorithmic thinking, and include detail on all the essential mathematical prerequisites, to offer a fresh and accessible way to learn. Practical applications are emphasized, with examples from disciplines including computer vision, natural language processing, economics, neuroscience, recommender systems, physics, and biology. Over 300 color illustrations are included and have been meticulously designed to enable an intuitive grasp of technical concepts, and over 100 in-depth coding exercises (in Python) provide a real understanding of crucial machine learning algorithms. A suite of online resources including sample code, data sets, interactive lecture slides, and a solutions manual are provided online, making this an ideal text both for graduate courses on machine learning and for individual reference and self-study.
| 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 |
Quem Deverá Comprar?
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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.
DESCRIÇÃO DO PRODUTO
Perguntas e respostas do cliente
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Pergunta:
What type of examples are included in the book?
Resposta: Examples are included from disciplines including computer vision, natural language processing, economics, neuroscience, recommender systems, physics, and biology. -
Pergunta:
What online resources are provided?
Resposta: A suite of online resources including sample code, data sets, interactive lecture slides, and a solutions manual are provided online. -
Pergunta:
Who is the target audience for this book?
Resposta: 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.
Avaliações e Classificações dos Clientes
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5 Estrela
68%
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4 Estrela
11%
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3 Estrela
6%
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2 Estrela
4%
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1 Estrela
11%
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Prós
- 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
Contras
- Some readers may find it quite dense to read.
CONFIANÇA NA PLATAFORMA E SEGURANÇA DO COMPRADOR
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Recursos e benefícios
- 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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