A Web Application that Uses Customer's Emotion to Recommend Food
About this project
What is this A simple web application that aims to recommend products to customers based on their emotions about other products. This was the final project to finish the 3rd year in university. Requirements Python 3.6+ Flask 1.0.2 for the entire web app passlib 1.7.1 for hashing passwords Keras 2.2.4 for 5-star sentiment analyzer Tensorflow 1.13.1 Keras backend (atleast in my case) FFmpeg for converting wav files to 16000Hz sample rate (install here) SciPy for the recommender system ( Used Matrix-Factorization ) NumPy Pandas Home Page Figure 1: Home page The customer at first is going to register for a new user and fill the form shown in Figure 2, once finished, you can see when he/she clicks at "Recommended Products" in the navigation bar shown in Figure 3, no products and content will be shown, that is because no rating ( or emotion ) has been successfully registered by the customer, the page will show as captured in Figure 4 Figure 2: Registration Form Figure 3: Navigation Bar Figure 4: No products available
From the project README on
GitHub
- Stars
- 18
- Forks
- 10
- License
- MIT
- Last push
- 1 May 2023
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