glasses
neuralforecast
| glasses | neuralforecast | |
|---|---|---|
| 2 | 84 | |
| 413 | 2,480 | |
| - | 4.9% | |
| 1.8 | 9.0 | |
| over 1 year ago | about 15 hours ago | |
| Jupyter Notebook | Python | |
| MIT License | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
glasses
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Are Open-sourced Implementations Sometimes Over-engineered?
Yes, they are. Take with a grain of salt, but researchers (usually) do not know how to code and (or) they don't care to properly share their work. Things that are learned in the first Computer Science bachelor year, like OOP, DRY, packages, good variables/function naming, are apparently not used in ml research. This is why I created my own library (https://github.com/FrancescoSaverioZuppichini/glasses), for me, good code means less time I have to spend working and more free time.
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[N] Facebook announced a new AI open-source called DeiT (A new technique to train computer vision models)
I have implemented most of the sota models in my library (https://github.com/FrancescoSaverioZuppichini/glasses). These are my 2 cents:
neuralforecast
- [D] Doubts on the implementation of LSTMs for timeseries prediction (like including weather forecasts)
- neuralforecast: NEW Data - star count:1877.0
- neuralforecast: NEW Data - star count:1773.0
- neuralforecast: NEW Data - star count:1749.0
- neuralforecast: NEW Data - star count:1696.0
- neuralforecast: NEW Data - star count:1663.0
What are some alternatives?
yolov5 - YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite
darts - A python library for user-friendly forecasting and anomaly detection on time series.
monodepth2 - [ICCV 2019] Monocular depth estimation from a single image
pytorch-forecasting - Time series forecasting with PyTorch
conformal_classification - Wrapper for a PyTorch classifier which allows it to output prediction sets. The sets are theoretically guaranteed to contain the true class with high probability (via conformal prediction).
statsforecast - Lightning ⚡️ fast forecasting with statistical and econometric models.
One-Piece-Image-Classifier - A quick image classifier trained with manually selected One Piece images.
nixtla - Python SDK for TimeGPT, a foundational time series model
gan-vae-pretrained-pytorch - Pretrained GANs + VAEs + classifiers for MNIST/CIFAR in pytorch.
Prophet - Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
HugsVision - HugsVision is a easy to use huggingface wrapper for state-of-the-art computer vision
flow-forecast - Deep learning PyTorch library for time series forecasting, classification, and anomaly detection (originally for flood forecasting).