Fast Laplacian Eigenmaps: lightweight multicore LE for non-linear dimensional reduction with minimal memory usage. Outperforms sklearn's implementation and escalates linearly beyond 10e6 samples.
MIT License
Scikit-learn friendly library to interpret, and prompt-engineer text datasets using large languag...
A PyTorch implementation of "SimGNN: A Neural Network Approach to Fast Graph Similarity Computat...
Data science tools for exploration, visualization, and model iteration.
Some fundamental machine learning and data-analysis techniques are explained through realistic ex...
A collection of code snippets from the publication Daily Dose of Data Science on Substack: http:/...
Diego: Data in, IntElliGence Out. A fast framework that supports the rapid construction of automa...
机器学习教程,本教程包含基于numpy、sklearn与tensorflow机器学习,也会包含利用spark、flink加快模型训练等用法。本着能够较全的引导读者入门机器学习。
Implementations of the machine learning algorithm with Python and numpy
2-2000x faster ML algos, 50% less memory usage, works on all hardware - new and old.
A Python package for common-nearest-neighbours clustering
Training Higgs Dataset with Keras - https://doi.org/10.5281/zenodo.13133945
Scikit-learn compatible estimation of general graphical models
An experiment about re-implementing supervised learning models based on shallow neural network ap...
Practice and tutorial-style notebooks covering wide variety of machine learning techniques
An intuitive library to add plotting functionality to scikit-learn objects.