Top AI Repos — open-source AI, indexed and scored
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Machine Learning algorithm implementations from scratch.
| Date | Stars |
|---|---|
| 2026-07-31 | 1634 |
| 2026-08-06 | 1633 |
Today
-1 stars today
This week
— stars this week
This month
— stars this month
Momentum
0.0
growth rate 0.00%/day
# ML algorithms from Scratch! > Machine Learning algorithm implementations from scratch. You can find Tutorials with the math and code explanations on my channel: [Here](https://www.youtube.com/playlist?list=PLqnslRFeH2Upcrywf-u2etjdxxkL8nl7E) ## Algorithms Implemented - KNN - Linear Regression - Logistic Regression - Naive Bayes - Perceptron - SVM - Decision Tree - Random Forest - Principal Component Analysis (PCA) - K-Means - AdaBoost - Linear Discriminant Analysis (LDA) ## Installation and usage. This project has 2 dependencies. - `numpy` for the maths implementation and writing the algorithms - `Scikit-learn` for the data generation and testing. - `Matplotlib` for the plotting. - `Pandas` for loading data. **NOTE**: Do note that, Only `numpy` is used for the implementations. Others help in the testing of code, and making it easy for us, instead of writing that too from scratch. You can install these using the command below! ```sh # Linux or MacOS pip3 install -r requirements.txt # Windows pip install -r requirements.txt ``` You can run the files as following. ```sh python -m mlfromscratch.<algorithm-file> ``` with `<algorithm-file>` being the valid filename of the algorithm without the extension. For example, If I want to run the Linear regression example, I would do `python -m mlfromscratch.linear_regression` ## Watch the Playlist [](https://www.youtube.com/watch?v=ngLyX54e1LU&list=PLqnslRFeH2Upcrywf-u2etjdxxkL8nl7E)
Excerpt of 1,529 characters
Read on GitHub
Patrick Loeber · @google-deepmind
24
1
1
Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:1fa44f6fd8625537, llm:Repository description: 'Machine Learning algorithm implementations from scratch.' Language: Python. No topics provided.
matched fp:1fa44f6fd8625537, llm:Repository description: 'Machine Learning algorithm implementations from scratch.' Language: Python. No topics provided.
matched fp:1fa44f6fd8625537, llm:Repository description: 'Machine Learning algorithm implementations from scratch.' Language: Python. No topics provided.