Guy Hoffman
Guy Hoffman
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Paper Cam Mechanism
Taken from the book
KARAKURI
How to Make Mechanical Paper Models That Move
Keisuke Saka; Translated by Eri Hamaji
us.macmillan.com/books/9780312566692
มุมมอง: 2 767

วีดีโอ

Choosing a variable to split on in decision tree learning
มุมมอง 1.4K7 ปีที่แล้ว
Choosing a variable to split on in decision tree learning
Filtering addendum
มุมมอง 3958 ปีที่แล้ว
Understanding the mechanisms of the two stages of Bayesian Filtering by looking at the Bayesian network elements that are involved in each stage.
The Two Stages of Bayes Filtering
มุมมอง 14K8 ปีที่แล้ว
An explanation of the two steps of Bayes Filtering (including Kalman Filtering, HMM Filtering, and Particle Filtering): Prediction and Correction. This video explains the principle and difference between the two stages, and exemplifies with a simple 1-dimensional example.
Bayes Nets Triads and Robot Control
มุมมอง 1708 ปีที่แล้ว
Bayes Nets Triads and Robot Control
Bayes Net Triads and robot control
มุมมอง 388 ปีที่แล้ว
Bayes Net Triads and robot control
Independence of Variables Intuition
มุมมอง 2348 ปีที่แล้ว
Independence of Variables Intuition
Conditional independence Intuition
มุมมอง 1.7K8 ปีที่แล้ว
We try to give a frequentist intuition to the sometimes confusing idea of Conditional Independence. How is it possible that two variables are not independent (i.e., knowing something about one tells you something about the probability of the other), but they *are* independent conditioned on a third one (it "explains away" their dependence). We use the technique of slicing and summing / averagin...
Bayesian Inference - Disease Detection
มุมมอง 7818 ปีที่แล้ว
A couple of ways to think about probabilistic inference in a multi-variable setting, using the "test for disease" example. We use the joint probability distribution, conditional probabilities, and marginal probabilities.

ความคิดเห็น

  • @lion87563
    @lion87563 ปีที่แล้ว

    Really good video. First video that I saw on youtube regarding Bayes Filter which represents these two models as discrete signals. This simplifies explanation

  • @Alex-zw9zc
    @Alex-zw9zc 4 ปีที่แล้ว

    How do you make this

  • @rakeshbakshi5899
    @rakeshbakshi5899 5 ปีที่แล้ว

    A clean explanation and a wonderful example. Thanks!

  • @donskanone
    @donskanone 5 ปีที่แล้ว

    Super nicely explained! Thank you.

  • @looper6394
    @looper6394 6 ปีที่แล้ว

    luckily I found this great introductive video on bayes filtering. thank you very much, finally I have a nice intuitive understanding of this process. it would be great if you could make another video and go from the discrete to continuous case.

  • @mehmetdilekify
    @mehmetdilekify 7 ปีที่แล้ว

    Hi Guy, This is very helpful. Would you consider making a video where you apply Kalman, HMM and Particle to the same problem changing the discrete/continuous assumption. It would be very helpful to see a kind of parallel run of these three algos. What are the differences, similarities etc.

  • @mini1o1
    @mini1o1 7 ปีที่แล้ว

    Hey this really helped, Thanks!

  • @ScottGrodberg1
    @ScottGrodberg1 7 ปีที่แล้ว

    Good illustration of how to solve. Very helpful!