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Adaptive Computation and Machine Learning series: Machine Learning : A Probabilistic Perspective (Hardcover)
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Adaptive Computation and Machine Learning series: Machine Learning : A Probabilistic Perspective (Hardcover)
Adaptive Computation and Machine Learning series: Machine Learning : A Probabilistic Perspective (Hardcover)
Nº de artículo: 62266460

Adaptive Computation and Machine Learning series: Machine Learning : A Probabilistic Perspective (Hardcover)

87% of respondents would recommend this to a friend

Nº de artículo: 62266460

DOP 9715

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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.

Detalles de producto

Discover the comprehensive introduction to machine learning with a probabilistic approach. Explore the latest developments in the field, including deep learning and L1 regularization. Get the MATLAB software package, PMTK, for implementing the models. Shop now at Ubuy Dominican Republic.
Manual & guide typeInstruction Manual
Book formatHardcover
Edition1
Skill levelBeginner
Pages1104
LanguageEnglish
BrandKevin P Murphy
Pub date2012-08-24
AuthorMIT Press
SubgenreMachine Theory
GenreComputing & Internet
Bisac subject headingComputers
Series titleAdaptive Computation and Machine Learning
Height9.1 in (23.1 cm)
EditorFrancis Bach
Educational levelCollege
Age groupAdult
Retail packagingSingle Piece
Original languagesEnglish
Item Weight3 lbs (1.36 kg)

Who Should Buy?

Suitable For
  • 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.

  • Academics and Researchers

    Useful for academics and researchers focusing on theoretical foundations and advancements in machine learning methodologies.

Not Suitable For
  • Beginner Learners

    Not suitable for beginners due to its complex concepts and assumed prior knowledge of statistics and math.

DESCRIPCIÓN DEL PRODUCTO

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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ventajas

  • Beginner-friendly with clear explanations
  • Comprehensive coverage of machine learning concepts
  • Suitable for college-level education
  • Durable hardcover format
  • Extensive reference material for learners

Contras

  • Might be overwhelming for absolute newcomers

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