sysidentpy
neural_prophet
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| sysidentpy | neural_prophet | |
|---|---|---|
| 7 | 5 | |
| 311 | 3,630 | |
| - | - | |
| 8.2 | 8.6 | |
| 17 days ago | 7 days ago | |
| Python | Python | |
| BSD 3-clause "New" or "Revised" License | MIT License |
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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.
sysidentpy
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Contribuição em biblioteca open source
Link para o site da documentação: SysIdentPy - SysIdentPy
- sysidentpy: A Python Package For System Identification Using NARMAX Models
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I'm giving out microgrants to open source projects for the third year in a row! Brag about your projects here so I can see them, big or small!
I'm the only maintainer, but I keep including new features (some exclusives, like the algorithm I've developed in my thesis to create NARMAX models), improving the code and documentation, and fixing bugs.
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A Comparison of Time Series Model Forecasting
benchmark codes: Welcome to SysIdentPy’s documentation! — NARMAX models
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Criei uma biblioteca open source para previsão de séries temporais
github: wilsonrljr/sysidentpy: A Python Package For System Identification Using NARMAX Models (github.com)
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Help with time series analysis
I built a package where you can build polynomial NARMAX models using the most used method for model selection of this class of models in the beckend. In addition, you can built NARX Neural Networks for forecasting problems (this is built on top of Pytorch) and you can use any model that have a fit/predict method (Catboost, any estimator from sklearn) in a NARX configuration to perform infinity-steps-ahead prediction. Maybe its worth a try. Here is the link of the package: GitHub - wilsonrljr/sysidentpy: A Python Package For System Identification Using NARMAX Models
neural_prophet
- Facebook Prophet: library for generating forecasts from any time series data
- Time series analysis of Bitcoin price in Python with fbprophet ?!
- 14 September 2021 - Daily Chat Thread
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[D] Stock prediction using lstm(plz help)
NeuralProphet
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Financial time-series data forecasting - any other tools besides Prophet?
Neural Prophet: https://github.com/ourownstory/neural_prophet
What are some alternatives?
pysindy - A package for the sparse identification of nonlinear dynamical systems from data
darts - A python library for user-friendly forecasting and anomaly detection on time series.
sktime - A unified framework for machine learning with time series
scikit-hts - Hierarchical Time Series Forecasting with a familiar API
rav1e - The fastest and safest AV1 encoder.
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.
forge - Lua scriptable build tool
orbit - A Python package for Bayesian forecasting with object-oriented design and probabilistic models under the hood.
space-nerds-in-space - Multi-player spaceship bridge simulator. Captain your starship through adventures with your friends. See https://smcameron.github.io/space-nerds-in-space
Prophet - Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
rpi-rgb-led-matrix - Controlling up to three chains of 64x64, 32x32, 16x32 or similar RGB LED displays using Raspberry Pi GPIO
Informer2020 - The GitHub repository for the paper "Informer" accepted by AAAI 2021.