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Torrent Details
Yaser-MachineLearning-CS156-Caltech
Category:
Other
Size:
3.13 GB
Seeders:
15
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Uploaded:
Oct 20, 2018
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Yaser-MachineLearning-CS156-Caltech
homework
final.pdf
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final_sol.pdf
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hw1.pdf
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hw1_sol.pdf
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hw2.pdf
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hw2_sol.pdf
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hw3.pdf
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hw3_sol.pdf
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hw4.pdf
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hw4_sol.pdf
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hw5.pdf
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hw5_sol.pdf
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hw6.pdf
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hw6_sol.pdf
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hw7.pdf
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hw7_sol.pdf
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hw8.pdf
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hw8_sol.pdf
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lectures
Lecture 01 - The Learning Problem-mbyG85GZ0PI.mp4
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Lecture 02 - Is Learning Feasible-MEG35RDD7RA.mp4
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Lecture 03 - The Linear Model I-FIbVs5GbBlQ.mp4
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Lecture 04 - Error and Noise-L_0efNkdGMc.mp4
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Lecture 05 - Training Versus Testing-SEYAnnLazMU.mp4
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Lecture 06 - Theory of Generalization-6FWRijsmLtE.mp4
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Lecture 07 - The VC Dimension-Dc0sr0kdBVI.mp4
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Lecture 08 - Bias-Variance Tradeoff-zrEyxfl2-a8.mp4
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Lecture 09 - The Linear Model II-qSTHZvN8hzs.mp4
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Lecture 10 - Neural Networks-Ih5Mr93E-2c.mp4
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Lecture 11 - Overfitting-EQWr3GGCdzw.mp4
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Lecture 12 - Regularization-I-VfYXzC5ro.mp4
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Lecture 13 - Validation-o7zzaKd0Lkk.mp4
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Lecture 14 - Support Vector Machines-eHsErlPJWUU.mp4
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Lecture 15 - Kernel Methods-XUj5JbQihlU.mp4
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Lecture 16 - Radial Basis Functions-O8CfrnOPtLc.mp4
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Lecture 17 - Three Learning Principles-EZBUDG12Nr0.mp4
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Lecture 18 - Epilogue-ihLwJPHkMRY.mp4
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slides
slides01.pdf
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slides02.pdf
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slides03.pdf
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slides04.pdf
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slides05.pdf
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slides06.pdf
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slides07.pdf
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slides08.pdf
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slides09.pdf
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slides10.pdf
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slides11.pdf
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slides12.pdf
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slides13.pdf
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slides14.pdf
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slides15.pdf
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slides16.pdf
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slides17.pdf
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slides18.pdf
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InfoHash:
8190B5122515AB158CD29CCDB33EA946A3E529F4
Last updated:
Jan 24, 2022
File count:
54 B
File Category:
1
Tags:
yaser, machinelearning, cs156, caltech
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