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.
Sunday, September 24, 2017
In tw's meeting we'll discuss non parametric estimating a CDF and its relation to learning - see https://drive.google.com/drive/folders/0BzUXUMab8u_ZQ0J3bGVWeHFsTjg?usp=sharing for details.
Sunday, August 20, 2017
For today's meeting. A simple NLP example before we get going on NLP.
https://drive.google.com/drive/folders/0BzUXUMab8u_ZZzcxWC1QRXhvSjA?usp=sharing
https://drive.google.com/drive/folders/0BzUXUMab8u_ZZzcxWC1QRXhvSjA?usp=sharing
Sunday, August 13, 2017
Information and decision trees - slides for today's meeting - https://drive.google.com/drive/folders/0BzUXUMab8u_Zc2ZhWmppRURnajg?usp=sharing
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