Machine Learning and Artificial Intelligence

The new edition of this popular professional book on artificial intelligence (ML) and machine learning (ML) has been revised for classroom or training use. The new edition provides comprehensive coverage of combined AI and ML theory and applications. Rather than looking at the field from only a theo...

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Detalhes bibliográficos
Autor principal: Joshi, Ameet V. (Author)
Autor Corporativo: SpringerLink (Online service)
Formato: Recurso Electrónico livro electrónico
Idioma:inglês
Publicado em: Cham : Springer International Publishing : Imprint: Springer, 2023.
Edição:2nd ed. 2023.
Assuntos:
Acesso em linha:https://doi.org/10.1007/978-3-031-12282-8
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Sumário:
  • Introduction
  • Introduction to AI and ML
  • Essential Concepts in Artificial Intelligence and Machine Learning
  • Data Understanding, Representation, and Visualization
  • Linear Methods
  • Perceptron and Neural Networks
  • Decision Trees
  • Support Vector Machines
  • Probabilistic Models
  • Dynamic Programming and Reinforcement Learning
  • Evolutionary Algorithms
  • Time Series Models
  • Deep Learning
  • Emerging Trends in Machine Learning
  • Unsupervised Learning
  • Featurization
  • Designing and Tuning
  • Model Pipelines
  • Performance Measurement
  • Classification
  • Regression
  • Ranking
  • Recommendations Systems
  • Azure Machine Learning
  • Open Source Machine Learning Libraries
  • Amazon’s Machine Learning Toolkit: Sagemaker
  • Conclusion.