Lightning ⚡️ fast forecasting with statistical and econometric models.
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Updated
Aug 5, 2024 - Python
Lightning ⚡️ fast forecasting with statistical and econometric models.
NeuralProphet: A simple forecasting package
If you can measure it, consider it predicted
Streamlit app to train, evaluate and optimize a Prophet forecasting model.
Web app to predict closing stock prices in real time using Facebook's Prophet time series algorithm with a multi-variate, single-step time series forecasting strategy.
Hierarchical Time Series Forecasting with a familiar API
Data Science algorithms for Qlik implemented as a Python Server Side Extension (SSE).
A library that unifies the API for most commonly used libraries and modeling techniques for time-series forecasting in the Python ecosystem.
Time Series Analysis and Forecasting in Python
This MVP data web app uses the Streamlit framework and Facebook's Prophet forecasting package to generate a dynamic forecast from your own data.
deploying an ML model to Heroku with FastAPI
Advance warning system for flood with rainfall analysis
In this project two models are build a Multivariate CNN-LSTM model using keras and tensorflow, ARIMA model, and FbProphet. In multivariate CNN-LSTM five feature are given as a input to the model and output as Closing price. Forecasted for the next 30 days. the dataset has been collected from Yahoo finance.
This project seeks to utilize the Deep Learning model, Long-Short Term Memory (LSTM) Neural Network algorithm, Time Series Models, ARIMA and FBProphet to predict stock prices.
A Project that uses Zillow research data on Quandl, Prophet for time series forecasting, Altair for vega-lite charts and Folium for an creating interactive map.
Project to predict stock prices with Recurrent Neural Network in TensorFlow with client input as web application (with Flask).
Arima, Sarima, LSTM, Prophet, DeepAR, Kats, Granger-causality, Autots
Plots stock prediction using fb-prophet with data from alphavantage
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