Podcasts Technology Learning Machines 101
Learning Machines 101

Learning Machines 101

83 episodes

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!

Podcasts

LM101-084: Ch6: How to Analyze the Behavior of Smart Dynamical Systems

Published: Jan. 5, 2021, 8:10 p.m.
Duration: 33 minutes 13 seconds

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LM101-083: Ch5: How to Use Calculus to Design Learning Machines

Published: Aug. 29, 2020, 1:21 p.m.
Duration: 34 minutes 22 seconds

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LM101-082: Ch4: How to Analyze and Design Linear Machines

Published: July 23, 2020, 10:57 p.m.
Duration: 29 minutes 5 seconds

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LM101-081: Ch3: How to Define Machine Learning (or at Least Try)

Published: April 9, 2020, 2:30 p.m.
Duration: 37 minutes 20 seconds

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LM101-080: Ch2: How to Represent Knowledge using Set Theory

Published: Feb. 29, 2020, 10:56 p.m.
Duration: 31 minutes 43 seconds

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LM101-079: Ch1: How to View Learning as Risk Minimization

Published: Dec. 24, 2019, 12:06 a.m.
Duration: 26 minutes 7 seconds

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LM101-078: Ch0: How to Become a Machine Learning Expert

Published: Oct. 24, 2019, 1:07 a.m.
Duration: 39 minutes 18 seconds

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LM101-077: How to Choose the Best Model using BIC

Published: May 2, 2019, 3:03 a.m.
Duration: 24 minutes 15 seconds

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LM101-076: How to Choose the Best Model using AIC and GAIC

Published: Jan. 23, 2019, 4:27 a.m.
Duration: 28 minutes 17 seconds

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LM101-075: Can computers think? A Mathematician's Response (remix)

Published: Dec. 12, 2018, 6:27 a.m.
Duration: 36 minutes 26 seconds

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LM101-074: How to Represent Knowledge using Logical Rules (remix)

Published: June 30, 2018, 2:35 a.m.
Duration: 19 minutes 22 seconds

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LM101-073: How to Build a Machine that Learns to Play Checkers (remix)

Published: April 25, 2018, 11:42 p.m.
Duration: 24 minutes 58 seconds

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LM101-072: Welcome to the Big Artificial Intelligence Magic Show! (Remix of LM101-001 and LM101-002)

Published: March 31, 2018, 2:23 a.m.
Duration: 22 minutes 7 seconds

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LM101-071: How to Model Common Sense Knowledge using First-Order Logic and Markov Logic Nets

Published: Feb. 23, 2018, 11:02 p.m.
Duration: 31 minutes 40 seconds

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LM101-070: How to Identify Facial Emotion Expressions in Images Using Stochastic Neighborhood Embedding

Published: Jan. 31, 2018, 11 p.m.
Duration: 32 minutes 4 seconds

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LM101-069: What Happened at the 2017 Neural Information Processing Systems Conference?

Published: Dec. 16, 2017, 4:51 p.m.
Duration: 23 minutes 20 seconds

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LM101-068: How to Design Automatic Learning Rate Selection for Gradient Descent Type Machine Learning Algorithms

Published: Sept. 26, 2017, 1:52 a.m.
Duration: 21 minutes 49 seconds

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LM101-067: How to use Expectation Maximization to Learn Constraint Satisfaction Solutions (Rerun)

Published: Aug. 21, 2017, 11 a.m.
Duration: 25 minutes 40 seconds

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LM101-066: How to Solve Constraint Satisfaction Problems using MCMC Methods (Rerun)

Published: July 17, 2017, 5 p.m.
Duration: 34 minutes

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LM101-065: How to Design Gradient Descent Learning Machines (Rerun)

Published: June 19, 2017, 3 p.m.
Duration: 30 minutes

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LM101-064: Stochastic Model Search and Selection with Genetic Algorithms (Rerun)

Published: May 15, 2017, 5 p.m.
Duration: 28 minutes 4 seconds

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LM101-063: How to Transform a Supervised Learning Machine into a Policy Gradient Reinforcement Learning Machine

Published: April 20, 2017, 4:16 a.m.
Duration: 22 minutes 4 seconds

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LM101-062: How to Transform a Supervised Learning Machine into a Value Function Reinforcement Learning Machine

Published: March 19, 2017, 1:52 a.m.
Duration: 31 minutes 5 seconds

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LM101-061: What happened at the Reinforcement Learning Tutorial? (RERUN)

Published: Feb. 23, 2017, 2:07 a.m.
Duration: 29 minutes 15 seconds

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LM101-060: How to Monitor Machine Learning Algorithms using Anomaly Detection Machine Learning Algorithms

Published: Jan. 23, 2017, 4:14 a.m.
Duration: 29 minutes 32 seconds

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LM101-059: How to Properly Introduce a Neural Network

Published: Dec. 21, 2016, 5:16 a.m.
Duration: 29 minutes 56 seconds

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LM101-058: How to Identify Hallucinating Learning Machines using Specification Analysis

Published: Nov. 23, 2016, 3:49 a.m.
Duration: 19 minutes 38 seconds

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LM101-057: How to Catch Spammers using Spectral Clustering

Published: Oct. 18, 2016, 3:44 a.m.
Duration: 19 minutes 54 seconds

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LM101-056: How to Build Generative Latent Probabilistic Topic Models for Search Engine and Recommender System Applications

Published: Sept. 20, 2016, 1:22 a.m.
Duration: 27 minutes 59 seconds

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LM101-055: How to Learn Statistical Regularities using MAP and Maximum Likelihood Estimation (Rerun)

Published: Aug. 16, 2016, 3:54 a.m.
Duration: 35 minutes 6 seconds

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LM101-054: How to Build Search Engine and Recommender Systems using Latent Semantic Analysis (RERUN)

Published: July 25, 2016, 7:41 p.m.
Duration: 29 minutes 35 seconds

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LM101-053: How to Enhance Learning Machines with Swarm Intelligence (Particle Swarm Optimization)

Published: July 11, 2016, 6:31 p.m.
Duration: 26 minutes 50 seconds

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LM101-052: How to Use the Kernel Trick to Make Hidden Units Disappear

Published: June 13, 2016, 10 a.m.
Duration: 28 minutes 57 seconds

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LM101-051: How to Use Radial Basis Function Perceptron Software for Supervised Learning[Rerun]

Published: May 24, 2016, 4:37 p.m.
Duration: 29 minutes 4 seconds

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LM101-050: How to Use Linear Machine Learning Software to Make Predictions (Linear Regression Software)[RERUN]

Published: May 4, 2016, 1:53 a.m.
Duration: 30 minutes 32 seconds

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LM101-049: How to Experiment with Lunar Lander Software

Published: April 22, 2016, 3:53 p.m.
Duration: 34 minutes 40 seconds

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LM101-048: How to Build a Lunar Lander Autopilot Learning Machine (Rerun)

Published: March 29, 2016, 1:40 a.m.
Duration: 31 minutes 27 seconds

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LM101-047: How Build a Support Vector Machine to Classify Patterns (Rerun)

Published: March 14, 2016, 11:53 p.m.
Duration: 35 minutes 29 seconds

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LM101-046: How to Optimize Student Learning using Recurrent Neural Networks (Educational Technology)

Published: Feb. 23, 2016, 4:55 a.m.
Duration: 23 minutes 19 seconds

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LM101-045: How to Build a Deep Learning Machine for Answering Questions about Images

Published: Feb. 8, 2016, 10:44 p.m.
Duration: 21 minutes 51 seconds

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LM101-044: What happened at the Deep Reinforcement Learning Tutorial at the 2015 Neural Information Processing Systems Conference?

Published: Jan. 26, 2016, 5:11 a.m.
Duration: 31 minutes 38 seconds

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LM101-043: How to Learn a Monte Carlo Markov Chain to Solve Constraint Satisfaction Problems (Rerun of Episode 22)

Published: Jan. 12, 2016, 3:50 a.m.
Duration: 27 minutes 38 seconds

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LM101-042: What happened at the Monte Carlo Markov Chain (MCMC) Inference Methods Tutorial at the 2015 Neural Information Processing Systems Conference?

Published: Dec. 29, 2015, 3:10 a.m.
Duration: 25 minutes 46 seconds

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LM101-041: What happened at the 2015 Neural Information Processing Systems Deep Learning Tutorial?

Published: Dec. 16, 2015, 4:44 a.m.
Duration: 29 minutes 38 seconds

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LM101-040: How to Build a Search Engine, Automatically Grade Essays, and Identify Synonyms using Latent Semantic Analysis

Published: Nov. 24, 2015, 6:14 a.m.
Duration: 28 minutes 15 seconds

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LM101-039: How to Solve Large Complex Constraint Satisfaction Problems (Monte Carlo Markov Chain and Markov Fields)[Rerun]

Published: Nov. 9, 2015, 10:44 p.m.
Duration: 35 minutes 17 seconds

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LM101-038: How to Model Knowledge Skill Growth Over Time using Bayesian Nets

Published: Oct. 27, 2015, 2:35 a.m.
Duration: 23 minutes 55 seconds

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LM101-037: How to Build a Smart Computerized Adaptive Testing Machine using Item Response Theory

Published: Oct. 12, 2015, 2 p.m.
Duration: 34 minutes 56 seconds

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LM101-036: How to Predict the Future from the Distant Past using Recurrent Neural Networks

Published: Sept. 28, 2015, 10:03 p.m.
Duration: 25 minutes 26 seconds

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LM101-035: What is a Neural Network and What is a Hot Dog?

Published: Sept. 15, 2015, 5:45 a.m.
Duration: 28 minutes 59 seconds

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LM101-034: How to Use Nonlinear Machine Learning Software to Make Predictions (Feedforward Perceptrons with Radial Basis Functions)[Rerun]

Published: Aug. 25, 2015, 12:08 a.m.
Duration: 29 minutes 4 seconds

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LM101-033: How to Use Linear Machine Learning Software to Make Predictions (Linear Regression Software)[RERUN]

Published: Aug. 10, 2015, 6:40 p.m.
Duration: 31 minutes 28 seconds

In this episode will explain how to download and use free machine learning software which can be downloaded from the website: www.learningmachines101.com. The software can be used to make predictions using your own data sets. Although we will continue to focus on critical theoretical concepts in machine learning in future episodes, it is always useful to actually experience how these concepts work in practice.This is a rerun of Episode 13.

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LM101-032: How To Build a Support Vector Machine to Classify Patterns

Published: July 13, 2015, 6 p.m.
Duration: 35 minutes 25 seconds

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LM101-031: How to Analyze and Design Learning Rules using Gradient Descent Methods (RERUN)

Published: June 21, 2015, 5 p.m.
Duration: 32 minutes 2 seconds

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LM101-030: How to Improve Deep Learning Performance with Artificial Brain Damage (Dropout and Model Averaging)

Published: June 8, 2015, 10:53 p.m.
Duration: 32 minutes 2 seconds

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LM101-029: How to Modernize Deep Learning with Rectilinear units, Convolutional Nets, and Max-Pooling

Published: May 25, 2015, 7:57 p.m.
Duration: 35 minutes 59 seconds

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LM101-028: How to Evaluate the Ability to Generalize from Experience (Cross-Validation Methods)[RERUN]

Published: May 11, 2015, noon
Duration: 35 minutes 6 seconds

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LM101-027: How to Learn About Rare and Unseen Events (Smoothing Probabilistic Laws)[RERUN]

Published: April 28, 2015, 3:10 a.m.
Duration: 39 minutes 42 seconds

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LM101-026: How to Learn Statistical Regularities (Rerun)

Published: April 14, 2015, 12:22 a.m.
Duration: 35 minutes 12 seconds

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LM101-025: How to Build a Lunar Lander Autopilot Learning Machine

Published: March 24, 2015, 1:35 a.m.
Duration: 31 minutes 29 seconds

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LM101-024: How to Use Genetic Algorithms to Breed Learning Machines

Published: March 10, 2015, 3:40 a.m.
Duration: 29 minutes 15 seconds

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LM101-023: How to Build a Deep Learning Machine

Published: Feb. 24, 2015, 4:13 a.m.
Duration: 42 minutes 45 seconds

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LM101-022: How to Learn to Solve Large Constraint Satisfaction Problems

Published: Feb. 10, 2015, 12:36 a.m.
Duration: 26 minutes 49 seconds

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LM101-021: How to Solve Large Complex Constraint Satisfaction Problems (Monte Carlo Markov Chain)

Published: Jan. 26, 2015, 8:12 p.m.
Duration: 35 minutes 11 seconds

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LM101-020: How to Use Nonlinear Machine Learning Software to Make Predictions

Published: Jan. 12, 2015, 11:26 p.m.
Duration: 27 minutes 21 seconds

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LM101-019 (Rerun): How to Enhance Intelligence with a Robotic Body (Embodied Cognition)

Published: Dec. 22, 2014, 7 a.m.
Duration: 36 minutes 13 seconds

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LM101-018: Can Computers Think? A Mathematician's Response (Rerun)

Published: Dec. 12, 2014, 8 a.m.
Duration: 36 minutes 40 seconds

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LM101-017: How to Decide if a Machine is Artificially Intelligent (Rerun)

Published: Nov. 24, 2014, 6 p.m.
Duration: 33 minutes 40 seconds

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LM101-016: How to Analyze and Design Learning Rules using Gradient Descent Methods

Published: Nov. 11, 2014, 1:57 a.m.
Duration: 31 minutes 21 seconds

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LM101-015: How to Build a Machine that Can Learn Anything (The Perceptron)

Published: Oct. 27, 2014, 12:39 p.m.
Duration: 30 minutes 7 seconds

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LM101-014: How to Build a Machine that Can Do Anything (Function Approximation)

Published: Oct. 13, 2014, 11:08 p.m.
Duration: 32 minutes 36 seconds

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LM101-013: How to Use Linear Machine Learning Software to Make Predictions (Linear Regression Software)

Published: Sept. 22, 2014, 10:46 p.m.
Duration: 30 minutes 35 seconds

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LM101-012: How to Evaluate the Ability to Generalize from Experience (Cross-Validation Methods)

Published: Sept. 9, 2014, 12:20 a.m.
Duration: 32 minutes 50 seconds

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LM101-008: How to Represent Beliefs Using Probability Theory

Published: Sept. 3, 2014, 8:27 p.m.
Duration: 30 minutes 41 seconds

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LM101-011: How to Learn About Rare and Unseen Events (Smoothing Probabilistic Laws)

Published: Aug. 26, 2014, 1:44 a.m.
Duration: 40 minutes 23 seconds

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LM101-010: How to Learn Statistical Regularities (MAP and maximum likelihood estimation)

Published: Aug. 12, 2014, 12:52 a.m.
Duration: 34 minutes 34 seconds

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LM101-009: How to Enhance Intelligence with a Robotic Body (Embodied Cognition)

Published: July 28, 2014, noon
Duration: 35 minutes 21 seconds

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LM101-007: How to Reason About Uncertain Events using Fuzzy Set Theory and Fuzzy Measure Theory

Published: June 23, 2014, 11:33 p.m.
Duration: 26 minutes 33 seconds

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LM101-006: How to Interpret Turing Test Results

Published: June 9, 2014, noon
Duration: 31 minutes 24 seconds

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LM101-005: How to Decide if a Machine is Artificially Intelligent (The Turing Test)

Published: May 27, 2014, 2:10 a.m.
Duration: 32 minutes 6 seconds

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LM101-004: Can computers think? A mathematician.s response

Published: May 12, 2014, noon
Duration: 34 minutes 26 seconds

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LM101-003: How to Represent Knowledge using Logical Rules

Published: April 29, 2014, 6:48 a.m.
Duration: 20 minutes 19 seconds

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LM101-002: How to Build a Machine that Learns to Play Checkers

Published: April 29, 2014, 6:36 a.m.
Duration: 24 minutes 24 seconds

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