Lightning ⚡️ fast forecasting with statistical and econometric models.

A Python package for Bayesian forecasting with object-oriented design and probabilistic models under the hood.

A statistical library designed to fill the void in Python's time series analysis capabilities, including the equivalent of R's auto.arima function.

Time series forecasting with machine learning models

Stock Market Prediction Web App based on Machine Learning and Sentiment Analysis of Tweets (API keys included in code). The front end of the Web App is based on Flask and Wordpress. The App forecasts stock prices of the next seven days for any given stock under NASDAQ or NSE as input by the user. Predictions are made using three algorithms: ARIM…

Automatically build ARIMA, SARIMAX, VAR, FB Prophet and XGBoost Models on Time Series data sets with a Single Line of Code. Created by Ram Seshadri. Collaborators welcome.

Modeltime unlocks time series forecast models and machine learning in one framework

Forecasting electric power load of Delhi using ARIMA, RNN, LSTM, and GRU models

Introduction to time series preprocessing and forecasting in Python using AR, MA, ARMA, ARIMA, SARIMA and Prophet model with forecast evaluation.

Simple python example on how to use ARIMA models to analyze and predict time series.

Timeseries for everyone

next version move to https://github.com/billchen198318/hillfog, bambooBSC is an opensource Balanced Scorecard (BSC) Business Intelligence (BI) Web platform. BSC's Vision, Perspectives, Objectives of strategy, Key Performance Indicators (KPIs), Strategy Map, and SWOT, PDCA & PDCA report, Time Series Analysis.

CryptoCurrency prediction using machine learning and deep learning

Book and material for the course "Time series analysis with Python" (STA-2003)

基于ARIMA时间序列的销量预测模型，实际预测准确率达90%以上，内含有测试记录和实际上线效果。

CryptoCurrency prediction using Deep Recurrent Neural Networks

The set of functions used for time series analysis and in forecasting.

ARIMA, SARIMA, SARIMAX and AutoARIMA models for time series analysis and forecasting in the browser and Node.js

Jupyter Notebooks Collection for Learning Time Series Models

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