Learning Machines 101
Summary: Smart machines based upon the principles of artificial intelligence and machine learning are now prevalent in our everyday life. For example, artificially intelligent systems recognize our voices, sort our pictures, make purchasing suggestions, and can automatically fly planes and drive cars. In this podcast series, we examine such questions such as: How do these devices work? Where do they come from? And how can we make them even smarter and more human-like? These are the questions that will be addressed in this podcast series!
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- Artist: Richard M. Golden, Ph.D., M.S.E.E., B.S.E.E.
- Copyright: Copyright (c) 2014-2019 by Richard M. Golden. All rights reserved.
Podcasts:
LM101-066: How to Solve Constraint Satisfaction Problems using MCMC Methods (Rerun)
LM101-065: How to Design Gradient Descent Learning Machines (Rerun)
LM101-064: Stochastic Model Search and Selection with Genetic Algorithms (Rerun)
LM101-063: How to Transform a Supervised Learning Machine into a Policy Gradient Reinforcement Learning Machine
LM101-062: How to Transform a Supervised Learning Machine into a Value Function Reinforcement Learning Machine
LM101-061: What happened at the Reinforcement Learning Tutorial? (RERUN)
LM101-060: How to Monitor Machine Learning Algorithms using Anomaly Detection Machine Learning Algorithms
LM101-059: How to Properly Introduce a Neural Network
LM101-058: How to Identify Hallucinating Learning Machines using Specification Analysis
LM101-057: How to Catch Spammers using Spectral Clustering
LM101-056: How to Build Generative Latent Probabilistic Topic Models for Search Engine and Recommender System Applications
LM101-055: How to Learn Statistical Regularities using MAP and Maximum Likelihood Estimation (Rerun)
LM101-054: How to Build Search Engine and Recommender Systems using Latent Semantic Analysis (RERUN)
LM101-053: How to Enhance Learning Machines with Swarm Intelligence (Particle Swarm Optimization)
LM101-052: How to Use the Kernel Trick to Make Hidden Units Disappear
