memorize
machine_learning_basics
memorize | machine_learning_basics | |
---|---|---|
3 | 5 | |
173 | 4,205 | |
3.5% | - | |
0.0 | 0.0 | |
over 1 year ago | 3 months ago | |
Jupyter Notebook | Jupyter Notebook | |
MIT License | MIT License |
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
- 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.
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From refold Anki settings to machine learning; few reflections on Anki algorithm
Source code: https://github.com/Networks-Learning/memorize
machine_learning_basics
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Bayesian linear regression in (plain) Python
A while back I open sourced a repository implementing fundamental machine learning algorithms in Python, along with the most important theoretical information. I originally created the repository for myself when preparing for AI residency interviews. You can find the original Reddit post here.
- Bayesian linear regression in Python
What are some alternatives?
fsrs4anki - A modern Anki custom scheduling based on Free Spaced Repetition Scheduler algorithm
Financial-Models-Numerical-Methods - Collection of notebooks about quantitative finance, with interactive python code.
100-Days-Of-ML-Code - 100 Days of ML Coding
borb-google-colab-examples - This repository contains some examples of using borb in google colab. These examples enable you to try out the features of borb without installing it on your system. They also ensure the system requirements and imports are all taken care of.
mango - Parallel Hyperparameter Tuning in Python
trulens - Evaluation and Tracking for LLM Experiments
rmi - A learned index structure
PyImpetus - PyImpetus is a Markov Blanket based feature subset selection algorithm that considers features both separately and together as a group in order to provide not just the best set of features but also the best combination of features
Time-series-classification-and-clustering-with-Reservoir-Computing - Library for implementing reservoir computing models (echo state networks) for multivariate time series classification and clustering.
perceptron-asm - A single-layer perceptron in x86 assembly to distinguish between circles and rectangles.
MachineLearningWithPython - Get started with Machine Learning with Python - An introduction with Python programming examples
iterative-grabcut - This algorithm uses a rectangle made by the user to identify the foreground item. Then, the user can edit to add or remove objects to the foreground. Then, it removes the background and makes it transparent.