Grokking: Generalization beyond Overfitting on small algorithmic datasets (Paper Explained)
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YouTubeYannic Kilcher
Grokking: Generalization beyond Overfitting on small algorithmic datasets (Paper Explained)
#grokking #openai #deeplearning Grokking is a phenomenon when a neural network suddenly learns a pattern in the dataset and jumps from random chance generalization to perfect generalization very suddenly. This paper demonstrates grokking on small algorithmic datasets where a network has to fill in binary tables. Interestingly, the learned ...
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Top 5 books to learn Algorithms 🔥1. “Introduction to Algorithms” by Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, and Clifford Stein2. “The Algorithm Design Manual” by Steven S. Skiena3. “Data Structures and Algorithms Made Easy: Data Structures and Algorithmic Puzzles” by Narasimha Karumanchi4. “Grokking Algorithms: An illustrated guide for programmers and other curious people” by Aditya Bhargava6. “Algorithms” by Robert Sedgewick and Kevin WayneSave for later 🔥💕
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