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Learning Machines 101
Richard M. Golden, Ph.D., M.S.E.E., B.S.E.E.
85 episodes
2 days ago
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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Technology
Science,
Mathematics
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All content for Learning Machines 101 is the property of Richard M. Golden, Ph.D., M.S.E.E., B.S.E.E. and is served directly from their servers with no modification, redirects, or rehosting. The podcast is not affiliated with or endorsed by Podjoint in any way.
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!
Show more...
Technology
Science,
Mathematics
Episodes (20/85)
Learning Machines 101
LM101-086: Ch8: How to Learn the Probability of Infinitely Many Outcomes
4 years ago
35 minutes 29 seconds

Learning Machines 101
LM101-085:Ch7:How to Guarantee your Batch Learning Algorithm Converges
4 years ago
30 minutes 51 seconds

Learning Machines 101
LM101-084: Ch6: How to Analyze the Behavior of Smart Dynamical Systems
4 years ago
33 minutes 13 seconds

Learning Machines 101
LM101-083: Ch5: How to Use Calculus to Design Learning Machines
5 years ago
34 minutes 22 seconds

Learning Machines 101
LM101-082: Ch4: How to Analyze and Design Linear Machines
5 years ago
29 minutes 5 seconds

Learning Machines 101
LM101-081: Ch3: How to Define Machine Learning (or at Least Try)
5 years ago
37 minutes 20 seconds

Learning Machines 101
LM101-080: Ch2: How to Represent Knowledge using Set Theory
5 years ago
31 minutes 43 seconds

Learning Machines 101
LM101-079: Ch1: How to View Learning as Risk Minimization
5 years ago
26 minutes 7 seconds

Learning Machines 101
LM101-078: Ch0: How to Become a Machine Learning Expert
6 years ago
39 minutes 18 seconds

Learning Machines 101
LM101-077: How to Choose the Best Model using BIC
6 years ago
24 minutes 15 seconds

Learning Machines 101
LM101-076: How to Choose the Best Model using AIC and GAIC
6 years ago
28 minutes 17 seconds

Learning Machines 101
LM101-075: Can computers think? A Mathematician's Response (remix)
6 years ago
36 minutes 26 seconds

Learning Machines 101
LM101-074: How to Represent Knowledge using Logical Rules (remix)
7 years ago
19 minutes 22 seconds

Learning Machines 101
LM101-073: How to Build a Machine that Learns to Play Checkers (remix)
7 years ago
24 minutes 58 seconds

Learning Machines 101
LM101-072: Welcome to the Big Artificial Intelligence Magic Show! (Remix of LM101-001 and LM101-002)
7 years ago
22 minutes 7 seconds

Learning Machines 101
LM101-071: How to Model Common Sense Knowledge using First-Order Logic and Markov Logic Nets
7 years ago
31 minutes 40 seconds

Learning Machines 101
LM101-070: How to Identify Facial Emotion Expressions in Images Using Stochastic Neighborhood Embedding
7 years ago
32 minutes 4 seconds

Learning Machines 101
LM101-069: What Happened at the 2017 Neural Information Processing Systems Conference?
7 years ago
23 minutes 20 seconds

Learning Machines 101
LM101-068: How to Design Automatic Learning Rate Selection for Gradient Descent Type Machine Learning Algorithms
8 years ago
21 minutes 49 seconds

Learning Machines 101
LM101-067: How to use Expectation Maximization to Learn Constraint Satisfaction Solutions (Rerun)
8 years ago
25 minutes 40 seconds

Learning Machines 101
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!