Skip to content

Visual insights which is a web application built using the library dash plotly and FLask functionalities

Notifications You must be signed in to change notification settings

SpaaceCadet/Visual-Insights

Repository files navigation

Visual-Insights

  • In this application we tried to deploy deep learning models for time series forecasting .
  • This Forecast concerns the prediction of energy price in the region of spain using time series models .
  • The models are : vanilla LSTM , stacked LSTM , the combination of LSTM and CNN model (Hybrid), The goal was to compare between the performance of these models .
  • The Application Visual insights represent an interface in which we integrated these models , to make predictions and make comparison .
  • It is built using dash plotly for better interactivity.
  • We tried to manipulate the architecture of dash by working on the flask layer to use a multipage model for good user experience , and add an authentification system using Mysql database ,SQLAlchemy, Flask login for this purpose .




  • This project was dockerized and decomposed into microservices using Tensorflow Serving , Mysql , and The web interface .
  • The Tensorflow Serving was used to serve our three models through apis,perform versioning . it's more suitable for production environements.


  • The each component has it's own dockerfile,configuration(secrets ..) , yaml file .

  • The whole architecture can be deployed as a kubernetes cluster .


About

Visual insights which is a web application built using the library dash plotly and FLask functionalities

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published