Kernel Methods for Machine Learning with Math and Python: 100 Exercises for Building Logic, (Paperback)
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Kernel Methods for Machine Learning with Math and Python: 100 Exercises for Building Logic, (Paperback)
The most crucial ability for machine learning and data science is mathematical logic for grasping their essence.
Kernel Methods for Machine Learning with Math and Python: 100 Exercises for Building Logic, (Paperback)
Бр. на производ: 254227667

Kernel Methods for Machine Learning with Math and Python: 100 Exercises for Building Logic, (Paperback)

Бр. на производ: 254227667

MKD 3948

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What Stands Out

Practical Exercises
Offers 100 hands-on exercises designed to reinforce concepts, enabling readers to apply theories to real-world problems and enhance their skills in kernel methods and machine learning logic.
Comprehensive Coverage
Delivers in-depth exploration of kernel methods, providing a solid mathematical foundation paired with Python coding examples, making complex topics accessible for learners with varying expertise.
Interactive Learning
Encourages active engagement through problem-solving, fostering critical thinking and promoting mastery in applying kernel techniques, which are essential for advancing in machine learning applications.

Детали за производот

Shop Kernel Methods for Machine Learning with Math and Python: 100 Exercises for Building Logic, (Paperback) online at a best price in North Macedonia. 437627824
Book formatPaperback
Fiction/nonfictionNon-Fiction
GenreComputing & Internet
Publication dateMay, 2022
Pages208
SubgenreArtificial Intelligence
Series titleNo Series
Edition2022 Edition
PublisherSpringer Nature Singapore
Original languagesEnglish
LanguageEnglish
Edu focusMathematics
Educational levelGeneral
Is collectibleN
Recording time0 min
Retail packagingSingle Piece
Assembled product dimensions (l x w x h)6.14 x 0.47 x 9.21 in (15.6 x 1.2 x 23.4 cm)
Assembled product weight0.7 lb (320 grams)
Bisac subject headingComputers

Who Should Buy?

Suitable For
  • Students in ML

    Ideal for students pursuing machine learning, providing practical exercises to solidify theoretical concepts through Python coding.

  • Data Scientists

    Useful for data scientists looking to enhance their understanding of kernel methods and their applications in real projects.

  • Self-learners

    Great resource for self-learners who want to practice machine learning at their own pace with guided exercises.

Not Suitable For
  • Beginners in Coding

    Not suitable for absolute beginners in programming, as prior knowledge of Python and machine learning is required.

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Kernel Methods for Machine Learning with Math and Python: 100 Exercises for Building Logic, (Paperback)

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Joe Suzuki All Books Editorial Review

Kernel Methods for Machine Learning with Math and Python: 100 Exercises for Building Logic offers a comprehensive guide for learners interested in artificial intelligence and machine learning. This paperback book, published in May 2022, spans 208 pages, focusing on mathematics and its application in the field. It provides 100 practical exercises designed to build logic in machine learning, making it suitable for general educational levels. Readers appreciate the clarity and practical approach of the content, affirming that it simplifies complex concepts for better understanding. This resource is especially beneficial for those seeking a non-fiction read that enhances their knowledge of computing and internet technologies.

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Добрите

  • Includes 100 practical exercises for hands-on learning
  • Focuses on mathematics in machine learning
  • Suitable for general educational levels
  • Clear and accessible explanations provided
  • Published by a reputable publisher, Springer

Конс

  • No collectible features noted for book enthusiasts

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MKD 3948

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Карактеристики и придобивки

  • Learn the fundamentals of kernel methods for machine learning.
  • Includes 100 carefully selected exercises with solutions.
  • Written in an easy-to-follow and self-contained style.
  • No prior knowledge of mathematics is assumed; suitable for beginners.
  • Covers distinct types of kernels, including RKHS and Gaussian processes.
  • Enhance your programming skills with source programs and running examples.

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