nptyping
Prophet
| nptyping | Prophet | |
|---|---|---|
| 1 | 221 | |
| 540 | 17,767 | |
| - | 0.5% | |
| 0.0 | 6.2 | |
| about 2 months ago | 1 day ago | |
| Python | Python | |
| MIT License | MIT License |
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.
nptyping
-
How to do static type checking for numpy in python (with both shape and data type)
I have looked on the internet a lot and there doesn't seem to be a good solution for this. A lot of people recommend nptyping but PyCharm complains about it. Is there a good static type checker for numpy arrays out there?
Prophet
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Moirai: A Time Series Foundation Model for Universal Forecasting
https://facebook.github.io/prophet/
"Prophet is a procedure for forecasting time series data based on an additive model where non-linear trends are fit with yearly, weekly, and daily seasonality, plus holiday effects. It works best with time series that have strong seasonal effects and several seasons of historical data. Prophet is robust to missing data and shifts in the trend, and typically handles outliers well."
- prophet: NEW Data - star count:17116.0
- prophet: NEW Data - star count:17082.0
- Facebook Prophet: library for generating forecasts from any time series data
- prophet: NEW Data - star count:16196.0
- prophet: NEW Data - star count:15889.0
What are some alternatives?
Crab - Crab is a flexible, fast recommender engine for Python that integrates classic information filtering recommendation algorithms in the world of scientific Python packages (numpy, scipy, matplotlib).
tensorflow - An Open Source Machine Learning Framework for Everyone
rwa - Machine Learning on Sequential Data Using a Recurrent Weighted Average
darts - A python library for user-friendly forecasting and anomaly detection on time series.
scikit-learn - scikit-learn: machine learning in Python
xgboost - Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow
Keras - Deep Learning for humans
greykite - A flexible, intuitive and fast forecasting library
gym - A toolkit for developing and comparing reinforcement learning algorithms.
MLflow - Open source platform for the machine learning lifecycle