bamboobsc

Lightning ⚡️ fast forecasting with statistical and econometric models.

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

A curated list of awesome Node providers and public RPC endpoints for Ethereum, BSC, Gnosis (xDAI), Fantom, Avalanche, KuCoin, Fuse, Harmony, Tezos, IoTeX, Arbitrum, Optimism and more :)

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.

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

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

Official GitHub Action for OpenSSF Scorecard.

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