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: ARIMA, LSTM, Linear Regression. The Web App combines the predicted prices of the next seven days with the sentiment analysis of tweets to give recommendation whether the price is going to rise or fall

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.

Time series forecasting for individual household power prediction: ARIMA, xgboost, RNN

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

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

Project analyzes Amazon Stock data using Python. Feature Extraction is performed and ARIMA and Fourier series models are made. LSTM is used with multiple features to predict stock prices and then sentimental analysis is performed using news and reddit sentiments. GANs are used to predict stock data too where Amazon data is taken from an API as Generator and CNNs are used as discriminator.

Applied an ARIMA-LSTM hybrid model to predict future price correlation coefficients of two assets

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

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

CryptoCurrency prediction using machine learning and deep learning

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

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.

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Augmented Reality image tracking with SwiftUI, RealityKit and ARKit 4.

Stock Prodiction by SVM & ARIMA

This is a project for predicting air pollutants in London by time series model, including lstm, bilstm, Convlstm, attention lstm, lightGBM and ARIMA

ARIMA is a Java open source project dedicated in the study model of ARIMA, AR, MA

used for Stock Prodiction&power prediction&Traffic prediction by ARIMA,xgboost,RNN,LSTM,TCN

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。

Code for paper: Block Hankel Tensor ARIMA for Multiple Short Time Series Forecasting (AAAI-20)

This is the code notebook for the blog post on using Python and Auto ARIMA

基于机器学习的股票投资算法，使用到了Auto-ARIMA、LSTM、SVM、Prophet、朴素贝叶斯、移动平均算法等多个算法，从信息收集、算法分析、回测等多个方面进行分析，从消息面、基本面、技术面三种分析方法进行分析。

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

CryptoCurrency prediction using Deep Recurrent Neural Networks

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