Here you can find Generic Python codes in the field of Data Science. You can watch the repositories by their topics:
Repository | Machine & Deep Learning | Algorithms | Geometry & GIS | Visualization | Projects |
---|---|---|---|---|---|
Conv-AutoEncoder | 🔮 | 📊 | 🚀 | ||
Mountaintops-DL | 🔮 | 🌍 | 🚀 | ||
Silhouette-Clustering | 🔮 | ||||
Graph-Feature-Propagation | 🔮 | ⚙️ | 📊 | ||
Cumulative-Heatmap | ⚙️ | 🌍 | 📊 | ||
Recursive-HeatMap | ⚙️ | 🌍 | 📊 | ||
Kmeans-Simulator | 🔮 | ⚙️ | 📊 | ||
My-Convex-Hull | ⚙️ | 🌍 | 📊 | ||
Poly-Regression | 🔮 | ⚙️ | 📊 | ||
Linear-SGD | 🔮 | ⚙️ | 📊 | ||
Histo-Regression | 🔮 | ⚙️ | |||
Wikipedia-BFS-crawler | ⚙️ | 🚀 | |||
Sector-Geometry | 🌍 | ||||
Github-Calendar | 📊 | 🚀 | |||
Convex-HDBSCAN | 🔮 | 🌍 | |||
Fire-Kites-Analysis | 🔮 | 🌍 | 📊 | 🚀 | |
3D GIFs | 📊 | ||||
Multiple-Densities | 📊 | ||||
Histogram Calculation | 📊 |
Each repository includes:
- The python code that developed as part of the project
- Implementation python file which demonstrates the use of the code
- Readme file that details exactly how it works (including visualization, explanations & math equations)
- Examples of importing and using the code
- Examples file to apply the code on them, as well as outputs files
- Descreption of required python libraries
- MIT using license