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Awesome GitHub RepositoriesLearning Pattern Optimizers
Algorithms that adjust model weights based on individual learning patterns to optimize memory retention.
Distinct from Parameter Optimizers: Specializes in educational memory weight updates rather than general ML training loss minimization.
Explore 1 awesome GitHub repository matching artificial intelligence & ml · Learning Pattern Optimizers. Refine with filters or upvote what's useful.
Awesome Learning Pattern Optimizers GitHub Repositories
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- open-spaced-repetition/fsrs4anki
open-spaced-repetition/fsrs4anki
3,990Voir sur GitHubThis project is a scheduling enhancement for Anki that implements the Free Spaced Repetition Scheduler algorithm. It serves as a replacement for traditional scheduling models, calculating review intervals to optimize long-term memory retention. The tool provides memory retention simulation to predict future review counts and study time based on historical data. It allows for the optimization of retention levels to balance study effort against memory persistence and supports custom scheduling overrides for specific decks. The system covers memory pattern analysis, workload prediction, and the
Optimizes the internal weights of the repetition algorithm by analyzing individual learning patterns.
Jupyter Notebookankianki-addondeep-learning
