https://github.com/tejas-130704/tejkart
A dynamic e-commerce platform that recommends products based on what you view, add to cart, and review. It understands your preferences through behavior, product similarity, and sentiment in reviews to deliver personalized shopping experiences.
https://github.com/tejas-130704/tejkart
aiml computer-vision django-rest-framework jwt-authentication nlp python react-js
Last synced: 2 months ago
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A dynamic e-commerce platform that recommends products based on what you view, add to cart, and review. It understands your preferences through behavior, product similarity, and sentiment in reviews to deliver personalized shopping experiences.
- Host: GitHub
- URL: https://github.com/tejas-130704/tejkart
- Owner: tejas-130704
- Created: 2025-04-08T14:15:00.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-04-08T14:50:45.000Z (over 1 year ago)
- Last Synced: 2025-04-08T15:35:18.839Z (over 1 year ago)
- Topics: aiml, computer-vision, django-rest-framework, jwt-authentication, nlp, python, react-js
- Language: JavaScript
- Homepage:
- Size: 115 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# 🛍️ Tejkart - Smart E-Commerce Platform with AI-Powered Recommendations
This is an intelligent E-Commerce web application that enhances the user shopping experience using Artificial Intelligence. It integrates **Computer Vision**, **Natural Language Processing (NLP)**, and **User Behavior Analysis** to deliver personalized product recommendations.
---
## 🚀 Features
### 🧠 AI-Powered Recommendation System
- **NLP-Based Similar Product Recommender**
- Uses product descriptions and metadata to find semantically similar items.
- **Computer Vision-Based Similarity**
- Uses CNN-based image feature extraction to recommend visually similar products.
- **Sentiment Analysis on Product Reviews**
- Automatically analyzes user reviews (positive/negative) using an RNN-based model trained on Amazon review data.
- Sentiment scores contribute to personalized recommendation logic.
- **User Interest Algorithm**
- Tracks user behavior like:
- Adding products to cart
- Searching for specific items
- Reviewing products
- Assigns **Interest Points** to product categories based on actions and sentiment.
- Dynamically recommends products from the most relevant categories.
### 🛒 E-Commerce Platform Essentials
- User registration & login with JWT Authentication
- Product browsing, search, and filtering
- Secure cart and checkout flow
- Product reviews and rating system
---
## 🛠️ Tech Stack
| Layer | Technology |
|-------|------------|
| **Frontend** | React.js, Tailwind CSS |
| **Backend** | Django, Django REST Framework |
| **Authentication** | JSON Web Tokens (JWT) |
| **ML/NLP** | Python, Scikit-learn, NLTK, RNN (for sentiment analysis), TF-IDF |
| **Computer Vision** | CNN (Convolutional Neural Networks), OpenCV |
| **Database** | PostgreSQL / SQLite |
---
## 🧠 Recommendation Workflow
```mermaid
graph TD
A[User Registers and Logs In] --> B[Views Product]
B --> C[NLP and CV Based Recommendations]
B --> D[Writes Review or Adds to Cart]
D --> E[Sentiment Analysis via RNN]
D --> F[Category Interest Tracking]
E --> G[Update Interest Points - Positive or Negative]
F --> G
G --> H[Personalized Category-Based Recommendations]
```
---
## ⚠️ Note About Repository Size & Missing Files
> Due to GitHub's storage limitations, some **large files including trained ML models** (`.h5`, `.pkl`, etc.) have **not been pushed to the repository**.
> The entire project exceeded GitHub's file size limits, so you may also notice **some major components (e.g., datasets, pre-trained models, or media folders) are missing**.
If you’re interested in running or testing the full application, feel free to contact me for access to the full project files and models.
---
## 💡 Future Enhancements
- Collaborative filtering with hybrid recommendation
- Recurrent user profiling with long-term interest tracking
- Deployment using Docker + CI/CD
- Admin dashboard with AI insights (product trends, user interest heatmaps)
---
## 📬 Contact
Created with ❤️ by **Tejas Narayan Jadhav**
📧 Email: [tejasjadhav130704@example.com]
🔗 LinkedIn: [https://www.linkedin.com/in/tejas-jadhav-385613256/](https://linkedin.com)
---