LM101-063: How to Transform a Supervised Learning Machine into a Policy Gradient Reinforcement Learning Machine | Apr 20, 2017 | Listen |

LM101-062: How to Transform a Supervised Learning Machine into a Value Function Reinforcement Learning Machine | Mar 19, 2017 | Listen |

LM101-061: What happened at the Reinforcement Learning Tutorial? (RERUN) | Feb 23, 2017 | Listen |

LM101-060: How to Monitor Machine Learning Algorithms using Anomaly Detection Machine Learning Algorithms | Jan 23, 2017 | Listen |

LM101-059: How to Properly Introduce a Neural Network | Dec 21, 2016 | Listen |

LM101-058: How to Identify Hallucinating Learning Machines using Specification Analysis | Nov 23, 2016 | Listen |

LM101-057: How to Catch Spammers using Spectral Clustering | Oct 18, 2016 | Listen |

LM101-056: How to Build Generative Latent Probabilistic Topic Models for Search Engine and Recommender System Applications | Sep 20, 2016 | Listen |

LM101-055: How to Learn Statistical Regularities using MAP and Maximum Likelihood Estimation (Rerun) | Aug 16, 2016 | Listen |

LM101-054: How to Build Search Engine and Recommender Systems using Latent Semantic Analysis (RERUN) | Jul 25, 2016 | Listen |

LM101-053: How to Enhance Learning Machines with Swarm Intelligence (Particle Swarm Optimization) | Jul 11, 2016 | Listen |

LM101-052: How to Use the Kernel Trick to Make Hidden Units Disappear | Jun 13, 2016 | Listen |

LM101-051: How to Use Radial Basis Function Perceptron Software for Supervised Learning[Rerun] | May 24, 2016 | Listen |

LM101-050: How to Use Linear Machine Learning Software to Make Predictions (Linear Regression Software)[RERUN] | May 04, 2016 | Listen |

LM101-049: How to Experiment with Lunar Lander Software | Apr 22, 2016 | Listen |

LM101-048: How to Build a Lunar Lander Autopilot Learning Machine (Rerun) | Mar 29, 2016 | Listen |

LM101-047: How Build a Support Vector Machine to Classify Patterns (Rerun) | Mar 14, 2016 | Listen |

LM101-046: How to Optimize Student Learning using Recurrent Neural Networks (Educational Technology) | Feb 23, 2016 | Listen |

LM101-045: How to Build a Deep Learning Machine for Answering Questions about Images | Feb 08, 2016 | Listen |

LM101-044: What happened at the Deep Reinforcement Learning Tutorial at the 2015 Neural Information Processing Systems Conference? | Jan 26, 2016 | Listen |

LM101-043: How to Learn a Monte Carlo Markov Chain to Solve Constraint Satisfaction Problems (Rerun of Episode 22) | Jan 12, 2016 | Listen |

LM101-042: What happened at the Monte Carlo Markov Chain (MCMC) Inference Methods Tutorial at the 2015 Neural Information Processing Systems Conference? | Dec 29, 2015 | Listen |

LM101-041: What happened at the 2015 Neural Information Processing Systems Deep Learning Tutorial? | Dec 16, 2015 | Listen |

LM101-040: How to Build a Search Engine, Automatically Grade Essays, and Identify Synonyms using Latent Semantic Analysis | Nov 24, 2015 | Listen |

LM101-039: How to Solve Large Complex Constraint Satisfaction Problems (Monte Carlo Markov Chain and Markov Fields)[Rerun] | Nov 09, 2015 | Listen |

LM101-038: How to Model Knowledge Skill Growth Over Time using Bayesian Nets | Oct 27, 2015 | Listen |

LM101-037: How to Build a Smart Computerized Adaptive Testing Machine using Item Response Theory | Oct 12, 2015 | Listen |

LM101-036: How to Predict the Future from the Distant Past using Recurrent Neural Networks | Sep 28, 2015 | Listen |

LM101-035: What is a Neural Network and What is a Hot Dog? | Sep 15, 2015 | Listen |

LM101-034: How to Use Nonlinear Machine Learning Software to Make Predictions (Feedforward Perceptrons with Radial Basis Functions)[Rerun] | Aug 25, 2015 | Listen |

LM101-033: How to Use Linear Machine Learning Software to Make Predictions (Linear Regression Software)[RERUN] | Aug 10, 2015 | Listen |

LM101-032: How To Build a Support Vector Machine to Classify Patterns | Jul 13, 2015 | Listen |

LM101-031: How to Analyze and Design Learning Rules using Gradient Descent Methods (RERUN) | Jun 21, 2015 | Listen |

LM101-030: How to Improve Deep Learning Performance with Artificial Brain Damage (Dropout and Model Averaging) | Jun 08, 2015 | Listen |

LM101-029: How to Modernize Deep Learning with Rectilinear units, Convolutional Nets, and Max-Pooling | May 25, 2015 | Listen |

LM101-028: How to Evaluate the Ability to Generalize from Experience (Cross-Validation Methods)[RERUN] | May 11, 2015 | Listen |

LM101-027: How to Learn About Rare and Unseen Events (Smoothing Probabilistic Laws)[RERUN] | Apr 28, 2015 | Listen |

LM101-026: How to Learn Statistical Regularities (Rerun) | Apr 14, 2015 | Listen |

LM101-025: How to Build a Lunar Lander Autopilot Learning Machine | Mar 24, 2015 | Listen |

LM101-024: How to Use Genetic Algorithms to Breed Learning Machines | Mar 10, 2015 | Listen |

LM101-023: How to Build a Deep Learning Machine | Feb 24, 2015 | Listen |

LM101-022: How to Learn to Solve Large Constraint Satisfaction Problems | Feb 10, 2015 | Listen |

LM101-021: How to Solve Large Complex Constraint Satisfaction Problems (Monte Carlo Markov Chain) | Jan 26, 2015 | Listen |

LM101-020: How to Use Nonlinear Machine Learning Software to Make Predictions | Jan 12, 2015 | Listen |

LM101-019 (Rerun): How to Enhance Intelligence with a Robotic Body (Embodied Cognition) | Dec 22, 2014 | Listen |

LM101-018: Can Computers Think? A Mathematician's Response (Rerun) | Dec 12, 2014 | Listen |

LM101-017: How to Decide if a Machine is Artificially Intelligent (Rerun) | Nov 24, 2014 | Listen |

LM101-016: How to Analyze and Design Learning Rules using Gradient Descent Methods | Nov 11, 2014 | Listen |

LM101-015: How to Build a Machine that Can Learn Anything (The Perceptron) | Oct 27, 2014 | Listen |

LM101-014: How to Build a Machine that Can Do Anything (Function Approximation) | Oct 13, 2014 | Listen |

LM101-013: How to Use Linear Machine Learning Software to Make Predictions (Linear Regression Software) | Sep 22, 2014 | Listen |

LM101-012: How to Evaluate the Ability to Generalize from Experience (Cross-Validation Methods) | Sep 09, 2014 | Listen |

LM101-008: How to Represent Beliefs Using Probability Theory | Sep 03, 2014 | Listen |

LM101-011: How to Learn About Rare and Unseen Events (Smoothing Probabilistic Laws) | Aug 26, 2014 | Listen |

LM101-010: How to Learn Statistical Regularities (MAP and maximum likelihood estimation) | Aug 12, 2014 | Listen |

LM101-009: How to Enhance Intelligence with a Robotic Body (Embodied Cognition) | Jul 28, 2014 | Listen |

LM101-007: How to Reason About Uncertain Events using Fuzzy Set Theory and Fuzzy Measure Theory | Jun 23, 2014 | Listen |

LM101-006: How to Interpret Turing Test Results | Jun 09, 2014 | Listen |

LM101-005: How to Decide if a Machine is Artificially Intelligent (The Turing Test) | May 27, 2014 | Listen |

LM101-004: Can computers think? A mathematician.s response | May 12, 2014 | Listen |

LM101-003: How to Represent Knowledge using Logical Rules | Apr 29, 2014 | Listen |

LM101-002: How to Build a Machine that Learns to Play Checkers | Apr 29, 2014 | Listen |