Cover Image

Machine Learning and Artificial Intelligence /

Show other versions (1)

This book provides comprehensive coverage of combined Artificial Intelligence (AI) and Machine Learning (ML) theory and applications. Rather than looking at the field from only a theoretical or only a practical perspective, this book unifies both perspectives to give holistic understanding. The firs...

Full description

Bibliographic Details
Main Author: Joshi, Ameet V. (Author)
Corporate Author: SpringerLink (Online service)
Format: eBook
Language:English
Published: Cham : Springer International Publishing : Imprint: Springer, 2020.
Edition:1st ed. 2020.
Subjects:
Electrical engineering.
Machine learning.
Computational intelligence.
Data mining.
Information storage and retrieval.
Big data.
Communications Engineering, Networks.
Machine Learning.
Computational Intelligence.
Data Mining and Knowledge Discovery.
Information Storage and Retrieval.
Big Data/Analytics.
Electronic books.
Online Access:Connect to the full text of this electronic book
Table of Contents:
  • Introduction
  • Part I Introduction to AI and ML
  • Essential concepts in AL and ML
  • Part II Techniques for Static Machine Learning Models
  • Perceptron and Neural Networks
  • Decision Trees
  • Advanced Decision Trees
  • Support Vector Machines
  • Probabilistic Models
  • Deep Learning
  • Part III Techniques for Dynamic Machine Learning Models
  • Autoregressive and Moving Average Models
  • Hidden Markov Models and Conditional Random Fields
  • Recurrent Neural Networks
  • Part IV Applications
  • Classification Regression
  • Ranking
  • Clustering
  • Recommendations
  • Next Best Actions
  • Designing ML Pipelines
  • Using ML Libraries
  • Azure Machine Learning Studio
  • Conclusions.