Sunday, October 29, 2017
Bootstrapping and confidence intervals
Confidence interval of your learning algorithm using bootstrapping. https://drive.google.com/drive/folders/0BzUXUMab8u_ZLTB6NnpiRUJZNUU
Monday, October 23, 2017
The plug-in principle and the R-S integral
We'll cover how to use the non parametric distribution estimate to estimate any statistic using the plug-in principle. we'll have to detour and understand what a R-S integral is - https://drive.google.com/drive/folders/0BzUXUMab8u_ZOHA2Szc3TFA4WHc
Sunday, October 15, 2017
Starting the discussion on how to test ML based systems. https://drive.google.com/drive/folders/0BzUXUMab8u_ZYnlNQVQ3TEVRa00
Sunday, October 1, 2017
In tomorrow's meeting we'll cover non-parametric density estimation. See https://drive.google.com/drive/folders/0BzUXUMab8u_ZcHRwcklpMFF0VHc?usp=sharing
for details and sample program.
for details and sample program.
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Our next ML study group meeting will take place on Monday the 8 th of October. I'll cover the contraction theorem. See relevant s...
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Ml crash directory Are you familiar with regression - https://m.youtube.com/watch?v=aq8VU5KLmkY ? One way to view Ml is regression on ster...
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We'll cover LDA in tw's meeting. Here is the slide - https://drive.google.com/open?id=1KRoCA4vo9H9oJOl3iD-qRqIHl9qQq9vf This is ...
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Whiteboard from today's meeting on Bayesian ML: Cox: P(A, B) = P(A|B)P(B) = P(B|A)P(A) => P(A|B) = [P(B|A)P(A)] / P(B) (Bayes) ...