query-selector
gluonts
| query-selector | gluonts | |
|---|---|---|
| 1 | 4 | |
| 75 | 4,297 | |
| - | 2.0% | |
| 3.7 | 8.7 | |
| 6 months ago | 9 days ago | |
| Python | Python | |
| Apache License 2.0 | 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.
query-selector
gluonts
-
Show HN: Auto Wiki v2 – Turn your codebase into a Wiki now with diagrams
https://github.com/awslabs/gluonts is a great candidate for a sample wiki. It is an OSS lib, not great documentation, very hard to RTFM (unlike, say, sklearn which already has a great wiki), doubtful that awslabs would pay to produce.
-
gluonts VS darts - a user suggested alternative
2 projects | 13 Apr 2023
-
[Q] `py.typed` and `.typesafe`
I was looking at [`gluonts`](https://github.com/awslabs/gluonts/tree/dev/src/gluonts/core) source code and I found a `py.typed` file. That is something I always put in my type-annotated modules: it's literally an empty file which denotes that the module is marked for "internal or external use in type checking" [mypy docs](https://mypy.readthedocs.io/en/stable/installed_packages.html?highlight=py.typed#creating-pep-561-compatible-packages). However, I never saw before the `.typesafe` file. What does it denote? Does it have to be used alongside a `py.typed`?
-
Cash-flow forecasting
-GluonTS
What are some alternatives?
neural_prophet - NeuralProphet: A simple forecasting package
darts - A python library for user-friendly forecasting and anomaly detection on time series.
LaTeX-OCR - pix2tex: Using a ViT to convert images of equations into LaTeX code.
pytorch-forecasting - Time series forecasting with PyTorch
flow-forecast - Deep learning PyTorch library for time series forecasting, classification, and anomaly detection (originally for flood forecasting).
tsai - Time series Timeseries Deep Learning Machine Learning Pytorch fastai | State-of-the-art Deep Learning library for Time Series and Sequences in Pytorch / fastai
sktime - A unified framework for machine learning with time series
statsforecast - Lightning ⚡️ fast forecasting with statistical and econometric models.
CrabNet - Predict materials properties using only the composition information!
neuralforecast - Scalable and user friendly neural :brain: forecasting algorithms.
how-do-vits-work - (ICLR 2022 Spotlight) Official PyTorch implementation of "How Do Vision Transformers Work?"
time-series-transformers-review - A professionally curated list of awesome resources (paper, code, data, etc.) on transformers in time series.