NeuralProphet: A simple forecasting package
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Updated
Sep 16, 2024 - Python
NeuralProphet: A simple forecasting package
Lightning ⚡️ fast forecasting with statistical and econometric models.
Streamlit app to train, evaluate and optimize a Prophet forecasting model.
Data Science algorithms for Qlik implemented as a Python Server Side Extension (SSE).
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.
If you can measure it, consider it predicted
Time Series Analysis and Forecasting in Python
Hierarchical Time Series Forecasting with a familiar API
This MVP data web app uses the Streamlit framework and Facebook's Prophet forecasting package to generate a dynamic forecast from your own data.
Advance warning system for flood with rainfall analysis
deploying an ML model to Heroku with FastAPI
A library that unifies the API for most commonly used libraries and modeling techniques for time-series forecasting in the Python ecosystem.
A data science project which predicts in how much time a service request will be solved.
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.
Project to predict stock prices with Recurrent Neural Network in TensorFlow with client input as web application (with Flask).
Forecasting models integrated in a web applications, built purely in Python
Plots stock prediction using fb-prophet with data from alphavantage
ICDSS Machine Learning Workshop Series: Machine Learning APIs
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