greykite
sktime
| greykite | sktime | |
|---|---|---|
| 3 | 8 | |
| 1,791 | 7,409 | |
| 0.3% | 1.1% | |
| 4.8 | 9.8 | |
| 3 months ago | about 21 hours ago | |
| Python | Python | |
| BSD 2-clause "Simplified" License | BSD 3-clause "New" or "Revised" License |
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greykite
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Hello reddit, what time series forecasting tools are you using?
I've been using greykite for forecasting some business metrics lately.
- Darts: Non-Facebook alternative for timeseries forecasting
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Predicting Daily Sales
Some other options to potentially look into are Facebook's Prophet and one of my new favorites, Greykite. These have some very useful functions to automatically fit seasonality and holidays. They also have the flexibility allowing you to custom define holiday periods (think times when certain promotions or campaigns were running) and other regressors (think macroeconomic data that may have a material effect on your sales).
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
What are some alternatives?
Prophet - Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
darts - A python library for user-friendly forecasting and anomaly detection on time series.
tslearn - The machine learning toolkit for time series analysis in Python
flow-forecast - Deep learning PyTorch library for time series forecasting, classification, and anomaly detection (originally for flood forecasting).
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-hts - Hierarchical Time Series Forecasting with a familiar API
scikit-learn - scikit-learn: machine learning in Python
sysidentpy - A Python Package For System Identification Using NARMAX Models
sktime-dl - DEPRECATED, now in sktime - companion package for deep learning based on TensorFlow
InceptionTime - InceptionTime: Finding AlexNet for Time Series Classification