Learning Machines 101
Richard M. Golden, Ph.D., M.S.E.E., B.S.E.E.
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Top 10 Learning Machines 101 Episodes
Goodpods has curated a list of the 10 best Learning Machines 101 episodes, ranked by the number of listens and likes each episode have garnered from our listeners. If you are listening to Learning Machines 101 for the first time, there's no better place to start than with one of these standout episodes. If you are a fan of the show, vote for your favorite Learning Machines 101 episode by adding your comments to the episode page.
LM101-017: How to Decide if a Machine is Artificially Intelligent (Rerun)
Learning Machines 101
11/24/14 • 33 min
This episode we discuss the Turing Test for Artificial Intelligence which is designed to determine if the behavior of a computer is indistinguishable from the behavior of a thinking human being. The chatbot A.L.I.C.E. (Artificial Linguistic Internet Computer Entity) is interviewed and basic concepts of AIML (Artificial Intelligence Markup Language) are introduced.
LM101-032: How To Build a Support Vector Machine to Classify Patterns
Learning Machines 101
07/13/15 • 35 min
In this 32nd episode of Learning Machines 101, we introduce the concept of a Support Vector Machine. We explain how to estimate the parameters of such machines to classify a pattern vector as a member of one of two categories as well as identify special pattern vectors called “support vectors” which are important for characterizing the Support Vector Machine decision boundary. The relationship of Support Vector Machine parameter estimation and logistic regression parameter estimation is also discussed. Check out this and other episodes as well as supplemental references to these episodes at the website: www.learningmachines101.com. Also follow us at twitter using the twitter handle: lm101talk.
LM101-025: How to Build a Lunar Lander Autopilot Learning Machine
Learning Machines 101
03/24/15 • 31 min
In this episode we consider the problem of learning when the actions of the learning machine can alter the characteristics of the learning machine’s statistical environment. We illustrate the solution to this problem by designing an autopilot for a lunar lander module that learns from its experiences!
Check out: www.learningmachines101.com to obtain transcripts of this podcast and download free machine learning software!
LM101-037: How to Build a Smart Computerized Adaptive Testing Machine using Item Response Theory
Learning Machines 101
10/12/15 • 34 min
In this episode, we discuss the problem of how to build a smart computerized adaptive testing machine using Item Response Theory (IRT). Suppose that you are teaching a student a particular target set of knowledge. Examples of such situations obviously occur in nursery school, elementary school, junior high school, high school, and college. However, such situations also occur in industry when top professionals in a particular field attend an advanced training seminar. All of these situations would benefit from a smart adaptive assessment machine which attempts to estimate a student’s knowledge in real-time. Such a machine could then use that information to optimize the choice and order of questions to be presented to the student in order to develop a customized exam for efficiently assessing the student’s knowledge level and possibly guiding instructional strategies. Both tutorial notes and advanced implementational notes can be found in the show notes at: www.learningmachines101.com .
![Learning Machines 101 - LM101-027: How to Learn About Rare and Unseen Events (Smoothing Probabilistic Laws)[RERUN]](https://storage.googleapis.com/goodpods-images-bucket/episode_images/09aaf989350ddc3b8310ce972e236b7e649801ffee1ada4655a633ed499489ad.avif)
LM101-027: How to Learn About Rare and Unseen Events (Smoothing Probabilistic Laws)[RERUN]
Learning Machines 101
04/28/15 • 39 min
In this episode of Learning Machines 101 we discuss the design of statistical learning machines which can make inferences about rare and unseen events using prior knowledge. Check out: www.learningmachines101.com to obtain transcripts of this podcast and download free machine learning software!
LM101-024: How to Use Genetic Algorithms to Breed Learning Machines
Learning Machines 101
03/10/15 • 29 min
In this episode we introduce the concept of learning machines that can self-evolve using simulated natural evolution into more intelligent machines using Monte Carlo Markov Chain Genetic Algorithms. Check out:
to obtain transcripts of this podcast and download free machine learning software!
LM101-056: How to Build Generative Latent Probabilistic Topic Models for Search Engine and Recommender System Applications
Learning Machines 101
09/20/16 • 27 min
In this NEW episode we discuss Latent Semantic Indexing type machine learning algorithms which have a PROBABILISTIC interpretation. We explain why such a probabilistic interpretation is important and discuss how such algorithms can be used in the design of document retrieval systems, search engines, and recommender systems. Check us out at: www.learningmachines101.com
and follow us on twitter at: @lm101talk
LM101-069: What Happened at the 2017 Neural Information Processing Systems Conference?
Learning Machines 101
12/16/17 • 23 min
This 69th episode of Learning Machines 101 provides a short overview of the 2017 Neural Information Processing Systems conference with a focus on the development of methods for teaching learning machines rather than simply training them on examples. In addition, a book review of the book “Deep Learning” is provided. #nips2017
LM101-008: How to Represent Beliefs Using Probability Theory
Learning Machines 101
09/03/14 • 30 min
Episode Summary: This episode focusses upon how an intelligent system can represent beliefs about its environment using fuzzy measure theory. Probability theory is introduced as a special case of fuzzy measure theory which is consistent with classical laws of logical inference.
LM101-059: How to Properly Introduce a Neural Network
Learning Machines 101
12/21/16 • 29 min
I discuss the concept of a “neural network” by providing some examples of recent successes in neural network machine learning algorithms and providing a historical perspective on the evolution of the neural network concept from its biological origins. For more details visit us at: www.learningmachines101.com
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FAQ
How many episodes does Learning Machines 101 have?
Learning Machines 101 currently has 85 episodes available.
What topics does Learning Machines 101 cover?
The podcast is about Mathematics, Podcasts, Technology and Science.
What is the most popular episode on Learning Machines 101?
The episode title 'LM101-080: Ch2: How to Represent Knowledge using Set Theory' is the most popular.
What is the average episode length on Learning Machines 101?
The average episode length on Learning Machines 101 is 30 minutes.
How often are episodes of Learning Machines 101 released?
Episodes of Learning Machines 101 are typically released every 20 days, 22 hours.
When was the first episode of Learning Machines 101?
The first episode of Learning Machines 101 was released on Apr 29, 2014.
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