gluonts
neuralforecast
gluonts | neuralforecast | |
---|---|---|
4 | 84 | |
4,308 | 2,432 | |
2.3% | 4.9% | |
8.7 | 9.0 | |
3 days 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.
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
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?
darts - A python library for user-friendly forecasting and anomaly detection on time series.
pytorch-forecasting - Time series forecasting with PyTorch
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
statsforecast - Lightning ⚡️ fast forecasting with statistical and econometric models.
nixtla - Python SDK for TimeGPT, a foundational time series model
time-series-transformers-review - A professionally curated list of awesome resources (paper, code, data, etc.) on transformers in time series.
Prophet - Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
sagemaker-python-sdk - A library for training and deploying machine learning models on Amazon SageMaker
flow-forecast - Deep learning PyTorch library for time series forecasting, classification, and anomaly detection (originally for flood forecasting).