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62266460
Adaptive Computation and Machine Learning series: Machine Learning : A Probabilistic Perspective (Hardcover)
87% of respondents would recommend this to a friend
Item #:
62266460
TZS 432439
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What Stands Out
Probabilistic Framework
Offers a comprehensive approach to machine learning using probabilistic models, enhancing the understanding of uncertainty in data and predictions, appealing to students and professionals in data science.
In-depth Coverage
Provides extensive coverage of essential machine learning techniques, algorithms, and applications, making it a critical resource for researchers, practitioners, and students looking to deepen their knowledge in the field.
Hands-On Examples
Includes practical examples and exercises that facilitate learning through real-world applications, helping readers to effectively apply concepts in their projects and deepen their analytical skills.
Product Details
| Manual & guide type | Instruction Manual |
| Book format | Hardcover |
| Edition | 1 |
| Skill level | Beginner |
| Pages | 1104 |
| Language | English |
| Brand | Kevin P Murphy |
| Pub date | 2012-08-24 |
| Author | MIT Press |
| Subgenre | Machine Theory |
| Genre | Computing & Internet |
| Bisac subject heading | Computers |
| Series title | Adaptive Computation and Machine Learning |
| Height | 9.1 in (23.1 cm) |
| Editor | Francis Bach |
| Educational level | College |
| Age group | Adult |
| Retail packaging | Single Piece |
| Original languages | English |
| Item Weight | 3 lbs (1.36 kg) |
Who Should Buy?
-
Graduate Students
Ideal for graduate students pursuing advanced studies in machine learning and statistics, seeking a comprehensive understanding.
-
Data Scientists
Beneficial for data scientists aiming to deepen their knowledge of probabilistic models in real-world applications.
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Academics and Researchers
Useful for academics and researchers focusing on theoretical foundations and advancements in machine learning methodologies.
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Beginner Learners
Not suitable for beginners due to its complex concepts and assumed prior knowledge of statistics and math.
Product Description
Adaptive Computation and Machine Learning series: Machine Learning : A Probabilistic Perspective (Hardcover)
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Kevin P Murphy Linear Algebra Books Editorial Review
Adaptive Computation and Machine Learning series: Machine Learning: A Probabilistic Perspective (Hardcover) is a comprehensive guide authored by Kevin P Murphy and published by MIT Press. This 1104-page manual is designed for beginners, making complex topics in machine theory more accessible to adult learners. It offers a blend of theoretical concepts and practical insights, suitable for college-level education. The hardcover format enhances durability, allowing for extensive use as a reference guide. With its clear language and expert guidance, this book supports readers in understanding the probabilistic underpinnings of machine learning and the computational frameworks that support them.
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Pros
- Beginner-friendly with clear explanations
- Comprehensive coverage of machine learning concepts
- Suitable for college-level education
- Durable hardcover format
- Extensive reference material for learners
Cons
- Might be overwhelming for absolute newcomers
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