neuralforecast
Prophet
neuralforecast | Prophet | |
---|---|---|
84 | 221 | |
2,432 | 17,767 | |
4.9% | 0.5% | |
9.0 | 6.2 | |
6 days ago | 1 day ago | |
Python | Python | |
Apache License 2.0 | 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.
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
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?
darts - A python library for user-friendly forecasting and anomaly detection on time series.
tensorflow - An Open Source Machine Learning Framework for Everyone
pytorch-forecasting - Time series forecasting with PyTorch
statsforecast - Lightning ⚡️ fast forecasting with statistical and econometric models.
scikit-learn - scikit-learn: machine learning in Python
nixtla - Python SDK for TimeGPT, a foundational time series model
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
flow-forecast - Deep learning PyTorch library for time series forecasting, classification, and anomaly detection (originally for flood forecasting).
greykite - A flexible, intuitive and fast forecasting library
mlforecast - Scalable machine 🤖 learning for time series forecasting.
MLflow - Open source platform for the machine learning lifecycle