Jupyter Notebook · Apache-2.0
curiousily/Getting-Things-Done-with-Pytorch
Jupyter Notebook tutorials on solving real-world problems with Machine Learning & Deep Learning using PyTorch. Topics: Face detection with Detectron 2, Time Series anomaly detection with LSTM Autoencoders, Object Detection with YOLO v5, Build your first Neural Network, Time Series forecasting for Coronavirus daily cases, Sentiment Analysis with BER
★ 2.5k
Stars
638 forks · 21 open issues
flat
Growth · measured
Stars counted between two of our own snapshots roughly a week apart. The repository page gives the exact span.
9.9
Momentum / 100
see the breakdown below
6y ago
Created
last push 2y ago
Star history
How this score was built
| Component | Weight | Earned | Why |
|---|---|---|---|
| Velocity | 55 | 0.0 | flat, log-scaled against a 750/day ceiling |
| Acceleration | 15 | 0.0 | needs 7-day and 30-day rates side by side |
| Freshness | 15 | 0.0 | last push 2y ago; decays to zero at 180 days |
| Scale | 15 | 9.9 | 2.5k stars, log-scaled against 150k — stops a 3-star repo topping the board |
| Momentum | 100 | 9.9 | sum of the above |
Detail
| Topics | anomaly-detectionbertcomputer-visioncoronavirusdeep-learningface-detectionface-recognitionlstmmachine-learningnlpobject-detectionpytorchsentiment-analysistime-seriestime-series-anomaly-detectiontime-series-forecastingtransfer-learningtransformertutorialyolo |
| Matched on | Computer Vision (object-detection) |
| Short window | +0 stars over 7 days = 0.0/day |
| Long window | +6 stars over 26 days = 0.2/day |
| Lifetime average | 1.02 stars/day over 2,470 days |
| First seen here | 2026-10-11 |
| Last read | 2d ago |