Renate
neural_prophet
| Renate | neural_prophet | |
|---|---|---|
| 1 | 5 | |
| 265 | 3,653 | |
| 0.8% | - | |
| 8.6 | 8.6 | |
| 4 months ago | 7 days ago | |
| Python | Python | |
| Apache License 2.0 | MIT License |
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Renate
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Renate: A Library for Real-World Continual Learning
Continual learning enables the incremental training of machine learning models on non-stationary data streams.While academic interest in the topic is high, there is little indication of the use of state-of-the-art continual learning algorithms in practical machine learning deployment. This paper presents Renate, a continual learning library designed to build real-world updating pipelines for PyTorch models. We discuss requirements for the use of continual learning algorithms in practice, from which we derive design principles for Renate. We give a high-level description of the library components and interfaces. Finally, we showcase the strengths of the library by presenting experimental results. Renate may be found at https://github.com/awslabs/renate.
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?
gluonts - Probabilistic time series modeling in Python
darts - A python library for user-friendly forecasting and anomaly detection on time series.
norse - Deep learning with spiking neural networks (SNNs) in PyTorch.
scikit-hts - Hierarchical Time Series Forecasting with a familiar API
zamba - A Python package for identifying 42 kinds of animals, training custom models, and estimating distance from camera trap videos
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.
orbit - A Python package for Bayesian forecasting with object-oriented design and probabilistic models under the hood.
Prophet - Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
sysidentpy - A Python Package For System Identification Using NARMAX Models
Informer2020 - The GitHub repository for the paper "Informer" accepted by AAAI 2021.
tslearn - The machine learning toolkit for time series analysis in Python
kafka-crypto-questdb - Using Kafka to track cryptocurrency price trends