memorize VS spaced-selection

Compare memorize vs spaced-selection and see what are their differences.

memorize

Code and real data for "Enhancing Human Learning via Spaced Repetition Optimization", PNAS 2019 (by Networks-Learning)

spaced-selection

Code and real data for "Large-scale randomized experiment reveals machine learning helps people learn and remember more effectively", npj Science of Learning 2021 (by Networks-Learning)
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memorize spaced-selection
3 1
173 30
3.5% -
0.0 2.6
over 1 year ago over 2 years ago
Jupyter Notebook Jupyter Notebook
MIT License -
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

memorize

Posts with mentions or reviews of memorize. We have used some of these posts to build our list of alternatives and similar projects.

spaced-selection

Posts with mentions or reviews of spaced-selection. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing memorize and spaced-selection you can also consider the following projects:

fsrs4anki - A modern Anki custom scheduling based on Free Spaced Repetition Scheduler algorithm

arxiv-vanity - Renders papers from arXiv as responsive web pages so you don't have to squint at a PDF.

arxiv.py - Python wrapper for the arXiv API