Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
---|---|---|---|---|---|---|---|---|---|---|
Phate | 421 | 2 | 14 | 10 months ago | 36 | August 13, 2018 | 23 | gpl-2.0 | Python | |
PHATE (Potential of Heat-diffusion for Affinity-based Transition Embedding) is a tool for visualizing high dimensional data. | ||||||||||
Vizuka | 100 | 6 years ago | Python | |||||||
Explore high-dimensional datasets and how your algo handles specific regions. | ||||||||||
Kwx | 57 | 5 months ago | 25 | January 28, 2023 | 11 | bsd-3-clause | Python | |||
BERT, LDA, and TFIDF based keyword extraction in Python | ||||||||||
Coursera_ml_da_specialization | 53 | 2 years ago | Jupyter Notebook | |||||||
Coursera Specialization: Machine Learning and Data Analysis (Yandex & MIPT) | ||||||||||
Machinera 2020 | 19 | 3 years ago | mit | |||||||
This is an AI Series where we will cover Machine Learning and Deep Learning topics from the very basics. | ||||||||||
Grae | 14 | 4 months ago | 3 | gpl-3.0 | Jupyter Notebook | |||||
Geometry Regularized Autoencoders (GRAE) for large-scale visualization and manifold learning | ||||||||||
Credit Card Fraud Detection | 9 | 5 years ago | gpl-3.0 | Jupyter Notebook | ||||||
It is Based on Anamoly Detection and by Using Deep Learning Model SOM which is an Unsupervised Learning Method to find patterns followed by the fraudsters. | ||||||||||
Unsupervised_analysis | 9 | 4 months ago | 23 | mit | Python | |||||
A general purpose Snakemake workflow to perform unsupervised analyses (dimensionality reduction & cluster analysis) and visualizations of high-dimensional data. | ||||||||||
Exploratory_data_analysis_and_ml_projects | 6 | 3 years ago | mit | Jupyter Notebook | ||||||
Several datasets are manipulated, visualized, and analyzed with well-known ML Algorithms to make predictions, clustering, or classifications. | ||||||||||
Heatgeo | 6 | 8 months ago | 1 | July 04, 2023 | mit | Jupyter Notebook | ||||
Embedding with the Heat-geodesic dissimilarity |