Learning Machines 101

Podcast készítő Richard M. Golden, Ph.D., M.S.E.E., B.S.E.E.

Kategóriák:

85 Epizód

  1. LM101-086: Ch8: How to Learn the Probability of Infinitely Many Outcomes

    Közzétéve: 2021. 07. 20.
  2. LM101-085:Ch7:How to Guarantee your Batch Learning Algorithm Converges

    Közzétéve: 2021. 05. 21.
  3. LM101-084: Ch6: How to Analyze the Behavior of Smart Dynamical Systems

    Közzétéve: 2021. 01. 05.
  4. LM101-083: Ch5: How to Use Calculus to Design Learning Machines

    Közzétéve: 2020. 08. 29.
  5. LM1010-082: Ch4: How to Analyze and Design Linear Machines

    Közzétéve: 2020. 07. 23.
  6. LM101-081: Ch3: How to Define Machine Learning (or at Least Try)

    Közzétéve: 2020. 04. 09.
  7. LM101-080: Ch2: How to Represent Knowledge using Set Theory

    Közzétéve: 2020. 02. 29.
  8. LM101-079: Ch1: How to View Learning as Risk Minimization

    Közzétéve: 2019. 12. 24.
  9. LM101-078: Ch0: How to Become a Machine Learning Expert

    Közzétéve: 2019. 10. 24.
  10. LM101-077: How to Choose the Best Model using BIC

    Közzétéve: 2019. 05. 02.
  11. LM101-076: How to Choose the Best Model using AIC and GAIC

    Közzétéve: 2019. 01. 23.
  12. LM101-075: Can computers think? A Mathematician's Response (remix)

    Közzétéve: 2018. 12. 12.
  13. LM101-074: How to Represent Knowledge using Logical Rules (remix)

    Közzétéve: 2018. 06. 30.
  14. LM101-073: How to Build a Machine that Learns to Play Checkers (remix)

    Közzétéve: 2018. 04. 25.
  15. LM101-072: Welcome to the Big Artificial Intelligence Magic Show! (Remix of LM101-001 and LM101-002)

    Közzétéve: 2018. 03. 31.
  16. LM101-071: How to Model Common Sense Knowledge using First-Order Logic and Markov Logic Nets

    Közzétéve: 2018. 02. 23.
  17. LM101-070: How to Identify Facial Emotion Expressions in Images Using Stochastic Neighborhood Embedding

    Közzétéve: 2018. 01. 31.
  18. LM101-069: What Happened at the 2017 Neural Information Processing Systems Conference?

    Közzétéve: 2017. 12. 16.
  19. LM101-068: How to Design Automatic Learning Rate Selection for Gradient Descent Type Machine Learning Algorithms

    Közzétéve: 2017. 09. 26.
  20. LM101-067: How to use Expectation Maximization to Learn Constraint Satisfaction Solutions (Rerun)

    Közzétéve: 2017. 08. 21.

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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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