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Masashi Sugiyama, Takashi Ishida - Introduction to Statistical Machine Learning, Häftad

Häftad, Engelska, 2027

Introduction to Statistical Machine Learning

Av Masashi Sugiyama, Takashi Ishida

2819 kr

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Beskrivning
Introduction to Statistical Machine Learning, Second Edition provides a general introduction to the fundamental concepts of statistics and probability that are used in describing machine learning algorithms, covering the two major approaches of machine learning techniques, generative methods and discriminative methods. The algorithms developed in the book include Python program code to provide readers with the necessary, practical skills needed to accomplish a wide range of data analysis tasks. The new edition also includes an all-new section on Deep Learning.

  • Provides the necessary background material to understand machine learning, including statistics, probability, linear algebra, and calculus
  • Presents complete coverage of the generative approach to statistical pattern recognition and the discriminative approach to statistical machine learning
  • Includes Python program code so that readers can test the algorithms numerically and acquire both mathematical and practical skills
Produktinformation
  • Utgivningsdatum: 2027-06-01
  • Mått: 191 x 235 x undefined mm
  • Vikt: 450 g
  • Format: Häftad
  • Språk: Engelska
  • Antal sidor: 650
  • Upplaga: 2
  • Förlag: Elsevier Science
  • ISBN: 9780443300325
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Mer information

Takashi Ishida is a Research Scientist at RIKEN AIP and an Associate Professor at The University of Tokyo. He received his PhD from the University of Tokyo, advised by Prof. Masashi Sugiyama. Prior to that, he received the MSc from the University of Tokyo and the Bachelor of Economics from Keio University. His research interests include statistical machine learning and its applications, with a focus on model and agent evaluation, alignment, and safety. Takashi Ishida is a Research Scientist at RIKEN AIP and an Associate Professor at The University of Tokyo. He received his PhD from the University of Tokyo, advised by Prof. Masashi Sugiyama. Prior to that, he received the MSc from the University of Tokyo and the Bachelor of Economics from Keio University. His research interests include statistical machine learning and its applications, with a focus on model and agent evaluation, alignment, and safety.

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