Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep learning.
Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep learning.
The purpose of this project is not to produce as optimized and computationally efficient algorithms as possible but rather to present the inner workings of them in a transparent and accessible way.
+--------+ | GA | +--------+ Description: Implementation of a Genetic Algorithm which aims to produce the user specified target string. This implementation calculates each candidate's fitness based on the alphabetical distance between the candidate and the target. A candidate is selected as a parent with probabilities proportional to the candidate's fitness. Reproduction is implemented as a single-point crossover…
Description and README excerpt from eriklindernoren/ML-From-Scratch on GitHub ↗.
eriklindernoren/ML-From-Scratch was first seen on GitHub · Trending Python today on Nov 1, 2026. Since then it has appeared in 8 checks on 2 different days. Its best position was #16 of 17, reached on Nov 1, 11:49 UTC. It dropped off the list after Nov 2, 08:49 UTC.
Position on GitHub · Trending Python today at every check (lower is better).
Best rank per day (UTC).
Platform metric as reported by GitHub.
Archived daily, weekly and monthly lists that include this entry.
Not at the moment. It was last on the list on Nov 2, 08:49 UTC, after 2 days of trending.
#16 on GitHub · Trending Python today, on Nov 1, 11:49 UTC. Trendoday checks this list every 180 minutes.
It was first seen on Nov 1, 2026 and has been on the list on 2 days (8 checks) since.
Mostly Python; it is licensed under MIT. It has 33.2k stars and 5529 forks.