Learning Machines 101
Ein Podcast von Richard M. Golden, Ph.D., M.S.E.E., B.S.E.E.
Kategorien:
85 Folgen
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LM101-026: How to Learn Statistical Regularities (Rerun)
Vom: 14.4.2015 -
LM101-025: How to Build a Lunar Lander Autopilot Learning Machine
Vom: 24.3.2015 -
LM101-024: How to Use Genetic Algorithms to Breed Learning Machines
Vom: 10.3.2015 -
LM101-023: How to Build a Deep Learning Machine
Vom: 24.2.2015 -
LM101-022: How to Learn to Solve Large Constraint Satisfaction Problems
Vom: 10.2.2015 -
LM101-021: How to Solve Large Complex Constraint Satisfaction Problems (Monte Carlo Markov Chain)
Vom: 26.1.2015 -
LM101-020: How to Use Nonlinear Machine Learning Software to Make Predictions
Vom: 12.1.2015 -
LM101-019 (Rerun): How to Enhance Intelligence with a Robotic Body (Embodied Cognition)
Vom: 22.12.2014 -
LM101-018: Can Computers Think? A Mathematician's Response (Rerun)
Vom: 12.12.2014 -
LM101-017: How to Decide if a Machine is Artificially Intelligent (Rerun)
Vom: 24.11.2014 -
LM101-016: How to Analyze and Design Learning Rules using Gradient Descent Methods
Vom: 11.11.2014 -
LM101-015: How to Build a Machine that Can Learn Anything (The Perceptron)
Vom: 27.10.2014 -
LM101-014: How to Build a Machine that Can Do Anything (Function Approximation)
Vom: 13.10.2014 -
LM101-013: How to Use Linear Machine Learning Software to Make Predictions (Linear Regression Software)
Vom: 22.9.2014 -
LM101-012: How to Evaluate the Ability to Generalize from Experience (Cross-Validation Methods)
Vom: 9.9.2014 -
LM101-008: How to Represent Beliefs Using Probability Theory
Vom: 3.9.2014 -
LM101-011: How to Learn About Rare and Unseen Events (Smoothing Probabilistic Laws)
Vom: 26.8.2014 -
LM101-010: How to Learn Statistical Regularities (MAP and maximum likelihood estimation)
Vom: 12.8.2014 -
LM101-009: How to Enhance Intelligence with a Robotic Body (Embodied Cognition)
Vom: 28.7.2014 -
LM101-007: How to Reason About Uncertain Events using Fuzzy Set Theory and Fuzzy Measure Theory
Vom: 23.6.2014
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!
