Open Machine Learning Course
Repository Index
47,133 repositories indexed
1–14 of 14 · Most stars
Visual analysis and diagnostic tools to facilitate machine learning model selection.
- machine-learning
- visual-analysis
- model-selection
- visualization
Java dataframe and visualization library
- dataframe
- data-frame
- java
- java-dataframe
An intuitive library to add plotting functionality to scikit-learn objects.
Owl - OCaml Scientific Computing @ https://ocaml.xyz
- matrix
- linear-algebra
- ndarray
- statistical-functions
:chart_with_upwards_trend: Adaptive: parallel active learning of mathematical functions
- adaptive-learning
- machine-learning
- python
- live-plots
A Unix, Windows, Raspberry Pi Object Speed Camera using python3, opencv, video streaming, motion tracking. Includes a Standalone Web Server , Image Search using opencv template match and a whiptail Admin Menu Interface Includes picam and webcam Plugins for motion track security camera configuration including rclone sync scripts.
- motion-tracking
- opencv
- rpi-camera
- speed-cam
Engine for AI/ML/Data tracking, visualization, explainability, drift detection, and dashboards for Polyaxon.
- pandas
- pandas-summary
- dataframes
- data-science
Usiigaci: stain-free cell tracking in phase contrast microscopy enabled by supervised machine learning
- tensorflow
- python3
- keras
- resnet-101
⬛ Python Individual Conditional Expectation Plot Toolbox
- machine-learning
- interpretability
Fish Audio Drama 3 text-to-speech on the TensorFold native CUDA engine for DGX Spark (GB10): recipe, engine patches, benchmarks. Built with Fish Audio.
GG.Net Data Visualization
A lightweight Python package for teaching computational methods through art history. Extract and analyze artist-specific works from WikiArt with built-in visualizations. Designed for digital humanities and computational design courses. Features genre/style analysis, matplotlib integration, and pedagogical clarity over algorithmic complexity.
- art-history
- color-analysis
- color-extraction
- color-palette
Machine learning model evaluation made easy: plots, tables, HTML reports, experiment tracking and Jupyter notebook analysis.