Learning Machines 101

Un pódcast de Richard M. Golden, Ph.D., M.S.E.E., B.S.E.E.

Categorías:

85 Episodo

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

    Publicado: 17/7/2017
  2. LM101-065: How to Design Gradient Descent Learning Machines (Rerun)

    Publicado: 19/6/2017
  3. LM101-064: Stochastic Model Search and Selection with Genetic Algorithms (Rerun)

    Publicado: 15/5/2017
  4. LM101-063: How to Transform a Supervised Learning Machine into a Policy Gradient Reinforcement Learning Machine

    Publicado: 20/4/2017
  5. LM101-062: How to Transform a Supervised Learning Machine into a Value Function Reinforcement Learning Machine

    Publicado: 19/3/2017
  6. LM101-061: What happened at the Reinforcement Learning Tutorial? (RERUN)

    Publicado: 23/2/2017
  7. LM101-060: How to Monitor Machine Learning Algorithms using Anomaly Detection Machine Learning Algorithms

    Publicado: 23/1/2017
  8. LM101-059: How to Properly Introduce a Neural Network

    Publicado: 21/12/2016
  9. LM101-058: How to Identify Hallucinating Learning Machines using Specification Analysis

    Publicado: 23/11/2016
  10. LM101-057: How to Catch Spammers using Spectral Clustering

    Publicado: 18/10/2016
  11. LM101-056: How to Build Generative Latent Probabilistic Topic Models for Search Engine and Recommender System Applications

    Publicado: 20/9/2016
  12. LM101-055: How to Learn Statistical Regularities using MAP and Maximum Likelihood Estimation (Rerun)

    Publicado: 16/8/2016
  13. LM101-054: How to Build Search Engine and Recommender Systems using Latent Semantic Analysis (RERUN)

    Publicado: 25/7/2016
  14. LM101-053: How to Enhance Learning Machines with Swarm Intelligence (Particle Swarm Optimization)

    Publicado: 11/7/2016
  15. LM101-052: How to Use the Kernel Trick to Make Hidden Units Disappear

    Publicado: 13/6/2016
  16. LM101-051: How to Use Radial Basis Function Perceptron Software for Supervised Learning[Rerun]

    Publicado: 24/5/2016
  17. LM101-050: How to Use Linear Machine Learning Software to Make Predictions (Linear Regression Software)[RERUN]

    Publicado: 4/5/2016
  18. LM101-049: How to Experiment with Lunar Lander Software

    Publicado: 22/4/2016
  19. LM101-048: How to Build a Lunar Lander Autopilot Learning Machine (Rerun)

    Publicado: 29/3/2016
  20. LM101-047: How Build a Support Vector Machine to Classify Patterns (Rerun)

    Publicado: 14/3/2016

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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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