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1. Introduction;
2. Prediction with expert advice;
3. Tight bounds for specific losses;
4. Randomized prediction;
5. Efficient forecasters for large classes of experts;
6. Prediction with limited feedback;
7. Prediction and playing games;
8. Absolute loss;
9. Logarithmic loss;
10. Sequential investment;
11. Linear pattern recognition;
12. Linear classification;
13. Appendix.
| Price | Condition | Delivery | Seller | Action |
| $99.99 | Digital |
| WonderClub |
James Walkley
reviewed Prediction, Learning, and Games on September 08, 2014
Prediction, Learning, and Games
Great intro to ML! For someone who doesn't have a formal Comp Sci background, this took a lot out of me. I found it helpful to stop after every chapter and listen to a more recent lecture to tie loose ends. Highly recommend reading this book in conjunction with professor Ng's ML intro course.
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Add Prediction, Learning, and Games, This important new text and reference for researchers and students in machine learning, game theory, statistics and information theory offers the first comprehensive treatment of the problem of predicting individual sequences. Unlike standard statistical , Prediction, Learning, and Games to the inventory that you are selling on WonderClubX
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Add Prediction, Learning, and Games, This important new text and reference for researchers and students in machine learning, game theory, statistics and information theory offers the first comprehensive treatment of the problem of predicting individual sequences. Unlike standard statistical , Prediction, Learning, and Games to your collection on WonderClub |
