Displaying 263 resources
Certification Certification
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Bayesian Learning

This lecture overviews Bayesian Learning that has many applications in pattern recognition and clustering. It covers the following topics in detail: Bayes probability theorem. Bayes decision rule. Bayesian classification.
Category
Systems, methodologies, hardware, and tools
Source
AI-OnDemand
Certification Certification
Online Course Online Course
Tutorial/How To/Guides Tutorial/How To/Guides

Decision Surfaces. Support Vector Machines

This lecture overviews Decision Surfaces and, in particular, Support Vector Machines that have many applications in Machine Learning and Pattern Recognition. It covers the following topics in detail: Decision surfaces. Hyperplanes.
Category
Systems, methodologies, hardware, and tools
Source
AI-OnDemand
Certification Certification
Online Course Online Course
Tutorial/How To/Guides Tutorial/How To/Guides

Agent Systems

This lecture overviews Agent Systems that has many applications in multi-party behavior modeling.
Category
Data for AI, Systems, methodologies, hardware, and tools, Reasoning and decision-making Technologies
Source
AI-OnDemand
Certification Certification
Online Course Online Course
Tutorial/How To/Guides Tutorial/How To/Guides

1D Convolutional Neural Networks

This lecture overviews 1D Convolutional Neural Networks that has many applications in 1D signal analysis.
Category
Data for AI, Systems, methodologies, hardware, and tools
Source
AI-OnDemand
Certification Certification
Online Course Online Course
Tutorial/How To/Guides Tutorial/How To/Guides

Graph-Based Pattern Recognition

This lecture overviews Graph-Based Pattern Recognition that has many applications in data clustering and dimensionality reduction.
Category
Systems, methodologies, hardware, and tools
Source
AI-OnDemand
Certification Certification
Online Course Online Course
Tutorial/How To/Guides Tutorial/How To/Guides

Introduction to Machine Learning

This lecture will cover the basic concepts of Machine Learning to alleviate inconsistencies towards concept and notation accuracy. Supervised, self-supervised, unsupervised, semi-supervised learning. Multi-task Machine Learning.
Category
Systems, methodologies, hardware, and tools
Source
AI-OnDemand