Learning Machines 101
A podcast by Richard M. Golden, Ph.D., M.S.E.E., B.S.E.E.
Categories:
85 Episoade
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LM101-086: Ch8: How to Learn the Probability of Infinitely Many Outcomes
Publicat: 20.07.2021 -
LM101-085:Ch7:How to Guarantee your Batch Learning Algorithm Converges
Publicat: 21.05.2021 -
LM101-084: Ch6: How to Analyze the Behavior of Smart Dynamical Systems
Publicat: 05.01.2021 -
LM101-083: Ch5: How to Use Calculus to Design Learning Machines
Publicat: 29.08.2020 -
LM1010-082: Ch4: How to Analyze and Design Linear Machines
Publicat: 23.07.2020 -
LM101-081: Ch3: How to Define Machine Learning (or at Least Try)
Publicat: 09.04.2020 -
LM101-080: Ch2: How to Represent Knowledge using Set Theory
Publicat: 29.02.2020 -
LM101-079: Ch1: How to View Learning as Risk Minimization
Publicat: 24.12.2019 -
LM101-078: Ch0: How to Become a Machine Learning Expert
Publicat: 24.10.2019 -
LM101-077: How to Choose the Best Model using BIC
Publicat: 02.05.2019 -
LM101-076: How to Choose the Best Model using AIC and GAIC
Publicat: 23.01.2019 -
LM101-075: Can computers think? A Mathematician's Response (remix)
Publicat: 12.12.2018 -
LM101-074: How to Represent Knowledge using Logical Rules (remix)
Publicat: 30.06.2018 -
LM101-073: How to Build a Machine that Learns to Play Checkers (remix)
Publicat: 25.04.2018 -
LM101-072: Welcome to the Big Artificial Intelligence Magic Show! (Remix of LM101-001 and LM101-002)
Publicat: 31.03.2018 -
LM101-071: How to Model Common Sense Knowledge using First-Order Logic and Markov Logic Nets
Publicat: 23.02.2018 -
LM101-070: How to Identify Facial Emotion Expressions in Images Using Stochastic Neighborhood Embedding
Publicat: 31.01.2018 -
LM101-069: What Happened at the 2017 Neural Information Processing Systems Conference?
Publicat: 16.12.2017 -
LM101-068: How to Design Automatic Learning Rate Selection for Gradient Descent Type Machine Learning Algorithms
Publicat: 26.09.2017 -
LM101-067: How to use Expectation Maximization to Learn Constraint Satisfaction Solutions (Rerun)
Publicat: 21.08.2017
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!
