Mathematics for Machine Learning Hardcover – 23 April 2020
This self-contained textbook bridges the gap between mathematical and machine learning texts, introducing the mathematical concepts with a minimum of prerequisites
Mathematics for Machine Learning Hardcover – 23 April 2020
Nº de artículo: 107702167

Mathematics for Machine Learning Hardcover – 23 April 2020

Nº de artículo: 107702167

GTQ 1071

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This self-contained textbook bridges the gap between mathematical and machine learning texts, introducing the mathematical concepts with a minimum of prerequisites
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What Stands Out

Comprehensive Coverage
This book provides an in-depth exploration of essential mathematical concepts for machine learning, ensuring readers gain a thorough understanding of underlying principles needed to excel.
Practical Applications
Each chapter connects theoretical mathematics to real-world machine learning applications, helping readers apply concepts effectively, bridging the gap between theory and practice.
Accessible Style
Written with clarity and precision, this hardcover edition caters to both beginners and experienced practitioners, making complex topics more approachable while maintaining rigorous academic standards.

Detalles de producto

Shop Mathematics for Machine Learning Hardcover – 23 April 2020 online at a best price in Guatemala. 1108470041
Item Weight3 lbs (1.36 kg)

Who Should Buy?

Suitable For
  • Aspiring Data Scientists

    Those looking to build a solid foundation in mathematics essential for data science and machine learning applications.

  • Graduate Students

    Perfect for graduate studies where a rigorous understanding of mathematical concepts relevant to machine learning is required.

  • Industry Professionals

    Professionals transitioning into machine learning roles who need to refresh or enhance their mathematical skills for practical application.

Not Suitable For
  • Beginner Learners

    Complete beginners in mathematics may struggle with the advanced concepts presented without prior foundational knowledge.

  • Casual Readers

    Those looking for light reading or casual learning won't find engaging material in this rigorous mathematical text.

  • Non-Technical Individuals

    Individuals without a technical or mathematical background may find the content too challenging and dense to comprehend.

DESCRIPCIÓN DEL PRODUCTO

Mathematics for Machine Learning Hardcover – 23 April 2020

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Preguntas y respuestas de los clientes

  • Pregunta: What topics are covered in the textbook?

    Respuesta: The textbook covers linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability, and statistics.
  • Pregunta: Who is the textbook suitable for?

    Respuesta: The textbook is suitable for students and professionals with a mathematical background or those learning the mathematics for the first time.
  • Pregunta: Are there any additional resources offered?

    Respuesta: Yes, programming tutorials are offered on the book's website.

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