maxim5/time-series-machine-learning
Machine learning models for time series analysis
This project helps cryptocurrency traders predict future price movements (like high, low, open, or close prices) for various cryptocurrencies. It takes historical market price data, specifically OHLC (Open-High-Low-Close) and volume information, and produces predictions for future price changes. This tool is designed for individual traders or analysts who want to apply machine learning to their trading strategies.
379 stars. No commits in the last 6 months.
Use this if you want to automatically predict daily or intraday percentage changes for cryptocurrency prices using advanced machine learning models.
Not ideal if you need to predict prices for traditional stocks, commodities, or other non-cryptocurrency assets, or if you prefer manual charting and technical analysis without automated predictions.
Stars
379
Forks
103
Language
Python
License
Apache-2.0
Category
Last pushed
Aug 19, 2021
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/maxim5/time-series-machine-learning"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Related frameworks
sktime/sktime
A unified framework for machine learning with time series
aeon-toolkit/aeon
A toolkit for time series machine learning and deep learning
Nixtla/neuralforecast
Scalable and user friendly neural :brain: forecasting algorithms.
tslearn-team/tslearn
The machine learning toolkit for time series analysis in Python
Nixtla/mlforecast
Scalable machine 🤖 learning for time series forecasting.