learn.kkinn.com - /Courses/ML/Machine Learning Pedro Domingos/08 Learning Theory/

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 2/25/2023  8:44 PM     61901297 1.  Boosting- The Details.mp4
 2/25/2023  8:47 PM     32378100 10.  Bias-Variance Decomposition for Zer -One Loss.mp4
 2/25/2023  8:48 PM     32521427 11.  Bias and Variance for Other Loss Functions.mp4
 2/25/2023  8:48 PM     50192730 12.  PAC Learning.mp4
 2/25/2023  8:49 PM    114029914 13.  How Many Examples Are Enough.mp4
 2/25/2023  8:48 PM     39768398 14.  Examples and Definition of PAC Learning.mp4
 2/25/2023  8:45 PM     88903088 2.  Error Correcting Output Coding.mp4
 2/25/2023  8:45 PM     88032418 3.  Stacking.mp4
 2/25/2023  8:45 PM     14347026 4.  Learning Theory.mp4
 2/25/2023  8:46 PM     89691075 5.  'No Free Lunch' Theorems.mp4
 2/25/2023  8:46 PM     48288031 6.  Practical Consequences of 'No Free Lunch'.mp4
 2/25/2023  8:47 PM     92368838 7.  Bias and Variance.mp4
 2/25/2023  8:47 PM     31724741 8.  Bias Variance Decomposition for Squared Loss.mp4
 2/25/2023  8:47 PM     88226384 9.  General Bias Variance Decomposition.mp4