sktime
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| sktime | Prophet | |
|---|---|---|
| 8 | 221 | |
| 7,387 | 17,720 | |
| 2.1% | 1.0% | |
| 9.8 | 6.2 | |
| 3 days ago | 15 days ago | |
| Python | Python | |
| BSD 3-clause "New" or "Revised" 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.
sktime
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Keras-tuner tuning hyperparam controlling feature size
I would recommend you to read the following paper: https://arxiv.org/abs/1909.04939 and their implementation: https://github.com/hfawaz/InceptionTime . Moreover, check out sktime: https://github.com/sktime/sktime
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Does anyone know a trusted Python package for applying Croston's Time series method?
I initially used the SkTime's Croston class SKTime Croston but when I try to get the fitted values using the steps in the discussion on github, the values are the same, a straight line throughout the in-sample to ou-of-sample predictions.
- Forecasting three months ahead.
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I Need Your Help: Convincing Reasons for Python over C# for ML Pipeline?
Time series -> https://github.com/alan-turing-institute/sktime have a look and have fun :)
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Good python time series libraries?
SKTime
- Scikit-Learn Version 1.0
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Sktime: Machine Learning for Time Series
https://github.com/alan-turing-institute/sktime
It provides specialized time series algorithms and scikit-learn compatible tools to build, tune and validate time series models for multiple learning problems.
sktime is built by an active open-source community, working together during regular meetings, workshops and sprints. For new contributors, we provide mentoring sessions and tutorials.
If you are interested in contributing or just a chat about the project, feel free to submit a PR or just reach out to us. We welcome all kinds of contributions: code, API design, testing, documentation, outreach, mentoring and more.
- Darts: Non-Facebook alternative for timeseries forecasting
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
tslearn - The machine learning toolkit for time series analysis in Python
Kats - Kats, a kit to analyze time series data, a lightweight, easy-to-use, generalizable, and extendable framework to perform time series analysis, from understanding the key statistics and characteristics, detecting change points and anomalies, to forecasting future trends.
scikit-learn - scikit-learn: machine learning in Python
scikit-hts - Hierarchical Time Series Forecasting with a familiar API
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
greykite - A flexible, intuitive and fast forecasting library
sysidentpy - A Python Package For System Identification Using NARMAX Models
MLflow - Open source platform for the machine learning lifecycle