Tag Archives: MAP estimation

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

Cartoon describing statistical learning with priors.

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LM101-055: How to Learn Statistical Regularities using MAP and ML Estimation Episode Summary: In this rerun of Episode 10, we discuss fundamental principles of learning in statistical environments including the design of learning machines that can use prior knowledge to facilitate and guide the learning of statistical regularities. Show Notes: Hello everyone! Welcome to the tenth podcast in… Read More »

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

Robot thinking about how to classify letters.

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LM101-032: How To Build a Support Vector Machine to Classify Patterns Episode Summary: 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… Read More »

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

Cartoon describing statistical learning with priors.

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How to Learn Statistical Regularities using MAP and ML Estimation Episode Summary: In this rerun of Episode 10, we discuss fundamental principles of learning in statistical environments including the design of learning machines that can use prior knowledge to facilitate and guide the learning of statistical regularities. Show Notes: Hello everyone! Welcome to the tenth podcast in the… Read More »

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

How do you compute the probability of rare and unseen events?

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Episode Summary: Today we address a strange yet fundamentally important question. How do you predict the probability of something you have never seen? Or, in other words, how can we accurately estimate the probability of rare events? Show Notes: Hello everyone! Welcome to the eleventh podcast in the podcast series Learning Machines 101. In this series of podcasts… Read More »

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

Cartoon describing statistical learning with priors.

Podcast: Play in new window | Download | Embed

Episode Summary: In this podcast episode, we discuss fundamental principles of learning in statistical environments including the design of learning machines that can use prior knowledge to facilitate and guide the learning of statistical regularities. Show Notes: Hello everyone! Welcome to the tenth podcast in the podcast series Learning Machines 101. In this series of podcasts my goal… Read More »