mnemosyne
free-spaced-repetition-scheduler
mnemosyne | free-spaced-repetition-scheduler | |
---|---|---|
19 | 11 | |
481 | 265 | |
2.5% | 7.5% | |
7.2 | 5.3 | |
12 days ago | about 1 month ago | |
Python | Python | |
GNU General Public License v3.0 or later | MIT License |
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mnemosyne
- The Mnemosyne Project: An Anki Alternative
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FSRS: A modern, efficient spaced repetition algorithm
I wonder if there is plan for this to land in Mnemosyne[1]. I prefer Mnemosyne over Anki because I can self-host the web-sync server.
1: https://mnemosyne-proj.org/
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How do you retain information when self learning?
I have tried using spaced repetition with Mnemosyne for math, specifically for learning Category Theory. It did help. Spaced repetition seems to work better for me if the answers to the questions are short (like learning Spanish vocabulary). When doing math, you often want to remember an entire definition, which might be too long to use spaced repetition flash cards effectively.
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Knot very smart
I've had good luck with spaced repetition using mnemosyne for lots of other stuff but haven't tried it for knots yet
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Hi, next week I have my first day as a software dev, and I'm kinda nervous.
Also, take the time to learn everyone's name and face. I use a flash card program like Mnemosyne to copy people's photos from the corporate directory. Learn them all the first week or even in the first couple of days.
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McMillan or PDG Promote?
https://mnemosyne-proj.org/ use this, make every relevant term a flash card and event a flash card. It takes forever to populate, but you learn on entry in addition to “study”.
- Consiglio sulle Flashcards?
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Ask HN: Recommendations for Spaced Repetition Beginners?
[15] https://mnemosyne-proj.org/ - OS alternative to Anki
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Best ways to study for initial CFI oral.
Anki is a spaced-repetition system based on Mnemosyne for studying flashcards in such a way that optimally loads facts into and maintains them in long-term memory. During daily study sessions, Anki shows flash cards, and you self-rate your ability to recall each correct answer. You review easier cards on a maintenance schedule, and Anki schedules the ones you have trouble with more frequently.
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Excited about Anki's Future Direction
Some time ago I saw several posts about a machine learning based scheduler for Anki. There is another project known as mnemosyne that conducts research into long term learning. Do you want similar changes to Anki's scheduler?
free-spaced-repetition-scheduler
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Anki – Powerful, intelligent flash cards
... https://github.com/open-spaced-repetition/fsrs4anki/wiki/The... ...
I'm not sure I believe we understand our own learning/memory anything like enough for this not to be total pseudoscience? Reminds me of A Beautiful Mind.
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FSRS: A modern, efficient spaced repetition algorithm
Libraries: https://github.com/open-spaced-repetition/free-spaced-repeti...
All are MIT licensed I believe, Anki is primarily AGPL
- The FSRS (Free Spaced Repetition Scheduler) Algorithm
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FSRS explained, part 1: What it is and how it works
Just read the wiki ¯\_(ツ)_/¯
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FSRS is supported in AnkiMobile now!
The model used by FSRS: https://github.com/open-spaced-repetition/fsrs4anki/wiki/Free-Spaced-Repetition-Scheduler
- How to use the next-generation spaced repetition algorithm FSRS on Anki?
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How did I publish a paper in ACMKDD as an undergraduate? A fantastic research experience on spaced repetition algorithm. Open source the code and dataset.
Also, sorry for nitpicking, but I just checked the code here, and I saw that you changed the formula for post-lapse stability, but you didn't update the formula in the description here.
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New progress in implementing the custom algorithm.
I have another one, also about difficulty. Look at the long "Stability updating formula after successful review" formula, there is a term D-b. This seems very counter-intuitive. A large value of D corresponds to an easy card, but thanks to that formula it will produce a very small change in stability. A small value of D corresponds to a difficult card, but according to that formula it will change stability a lot.
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Implement a new spaced repetition algorithm based on anki custom scheduling.
So I checked this and it seems that there's a whole bunch of different parameters (initial difficulty, initial stability, etc), and a lot of them are constant. So the next step would be to use some kind of optimization algorithm, like gradient descent, to optimize those parameters based on user's review history, right?
What are some alternatives?
anki - Anki's shared backend and web components, and the Qt frontend
fsrs4anki - A modern Anki custom scheduling based on Free Spaced Repetition Scheduler algorithm
Anki-Android - AnkiDroid: Anki flashcards on Android. Your secret trick to achieve superhuman information retention.
highlight-search-results - Highlight Search Results in the Browser add-on for Anki
anki-manual - Anki's manual
fsrs4anki-helper - An Anki add-on that reschedules all cards via FSRS4Anki scheduler
SM-15 - Spaced repetition for memorizing tons of things.
autoEaseFactor - Adjust ease factors in Anki based off of performance in order to hit a target success rate.
roamsr - Spaced Repetition in Roam Research
SSP-MMC - A Stochastic Shortest Path Algorithm for Optimizing Spaced Repetition Scheduling
ReeePlayer - Anki-like app for spaced repetition of video clips
tatoeba-to-anki - Creates Anki Flash cards from Tatoeba sentences, ordering them by difficulty and downloading audio