memorize
reinforcement_learning_course_materials
| memorize | reinforcement_learning_course_materials | |
|---|---|---|
| 3 | 1 | |
| 173 | 902 | |
| 3.5% | 0.4% | |
| 0.0 | 8.3 | |
| over 1 year ago | 9 days ago | |
| Jupyter Notebook | Jupyter Notebook | |
| MIT License | MIT License |
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memorize
- Understanding specific scientific paper with algorithm for spaced repetition learning
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I think the spaced repetition community should up it's research game, and implement the findings.
It's been long known to researchers that longer interval usually = better retention, with no clear diminishing returns, yet Anki's default intervals are extremely short. Most Anki bloggers and "influencers" give advice about Anki settings based on personal experience and gut feelings, even though we have OPEN DATA, even by Duolingo, analyzed with state of the art statistical methods demonstrating that there is much improvement to be made.
-
From refold Anki settings to machine learning; few reflections on Anki algorithm
Source code: https://github.com/Networks-Learning/memorize
reinforcement_learning_course_materials
What are some alternatives?
fsrs4anki - A modern Anki custom scheduling based on Free Spaced Repetition Scheduler algorithm
ML-Prediction-LoL - In this project I implemented two machine learning algorithms to predicts the outcome of a League of Legends game.
learn-monogame.github.io - Documentation to learn MonoGame from the ground up.
BestPractices - Things that you should (and should not) do in your Materials Informatics research.
human-memory - Course materials for Dartmouth course: Human Memory (PSYC 51.09)
LlamaIndex-course - Learn to build and deploy AI apps.
get-started-with-JAX - The purpose of this repo is to make it easy to get started with JAX, Flax, and Haiku. It contains my "Machine Learning with JAX" series of tutorials (YouTube videos and Jupyter Notebooks) as well as the content I found useful while learning about the JAX ecosystem.
gds_env - A containerised platform for Geographic Data Science
JustEnoughScalaForSpark - A tutorial on the most important features and idioms of Scala that you need to use Spark's Scala APIs.
ml-course - Open Machine Learning course
feature-engineering-tutorials - Data Science Feature Engineering and Selection Tutorials
ppde642 - USC urban data science course series with Python and Jupyter