Description : We have developed a Product which aims to provide a one step solution to both brands and its customers. We have built an Improved Recommendation System based on Embeddings of user and product which we develop using history, wishlist, intrests etc. Our Recommendation System solves one of the major problem faced by Modern Day Recommendation system i.e. recommendations of False Positives. We solved this problem by taking weighted labels of different categories. By using this technique we were able to achieve minimal number of False Positives, with improved number of True positives. Our Product also features a completely automated data analysis and visualisation solutions. We provide automatic clustering of users into an optimal number of clusters along with proper visualisation of data and also each cluster is provided with proper description along with summary. Even third - party vendors can use our website by providing us with the csv file of their data. Different form of data analysis are automated by our webapp. Thus we are transforming the world of Data Science into a compeletly automated webapp.
Intructions to run :
- Run python manage.py runserver.
- Start your webapp in your browser at : http://127.0.0.1:8000