https://github.com/swatiupadhyay/horoscope-predictor
ML-powered zodiac horoscope predictor with SVM and Flask ✨
https://github.com/swatiupadhyay/horoscope-predictor
flask horoscope machine-learning ml-app project python svm zodiac
Last synced: 2 months ago
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ML-powered zodiac horoscope predictor with SVM and Flask ✨
- Host: GitHub
- URL: https://github.com/swatiupadhyay/horoscope-predictor
- Owner: SwatiUpadhyay
- Created: 2025-04-07T20:48:20.000Z (6 months ago)
- Default Branch: main
- Last Pushed: 2025-04-07T20:54:23.000Z (6 months ago)
- Last Synced: 2025-04-10T02:54:36.309Z (6 months ago)
- Topics: flask, horoscope, machine-learning, ml-app, project, python, svm, zodiac
- Language: CSS
- Homepage:
- Size: 2.85 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# 🔮 Horoscope Predictor
Welcome to **Horoscope Predictor**, your cosmic bestie powered by machine learning and sprinkled with stardust. ✨
Choose your zodiac sign and reveal a personalized horoscope — trained on real data, delivered with love (and an SVM model behind the scenes).
Built using Flask, HTML/CSS/JS, and a trained **SVM classifier**, this app bridges the mystical with the mathematical. ♡
---
## 🌟 Features
- 🔮 Predicts your horoscope based on your selected zodiac sign
- 💻 Trained using real horoscope data (SVM, 93.97% accuracy baby!)
- 🌈 Clean, dreamy UI with glowy animations
- 🧠 Integrated ML model via Flask backend
- 💫 Super smooth user experience (with a cute lil reveal button!)
---
## 💽 Tech Stack
| Frontend | Backend | Machine Learning |
|----------------|----------------|---------------------------------|
| HTML, CSS, JS | Python + Flask | SVM Classifier (scikit-learn) |
---
## 🧠 How It Works
1. User picks a zodiac sign from the dropdown ♒️
2. The sign is sent via POST request to Flask backend 🔁
3. Flask returns a matching horoscope from a curated horoscope bank 🌙
4. The app displays it with animation + ✨vibes✨
> *Bonus*: The model was trained on a dataset of over **5,000 horoscope entries**, using SVM, Naive Bayes, and Random Forest.
> **SVM** gave the best results and is the **only model used in the app**.
---
## 🚀 Run It Locally
Clone the repo and feel the universe unfold:
```bash
git clone https://github.com/yourusername/horoscope-predictor.git
cd horoscope-predictor
Install the necessary dependencies:
pip install -r requirements.txt
Then run the Flask app:
python app.py
Open your browser and go to http://127.0.0.1:5000 to reveal your fate ✨
🗂 Project Structure
horoscope-predictor/
├── static/
│ ├── css/
│ │ └── style.css
│ ├── js/
│ │ └── script.js
├── templates/
│ └── index.html
├── models/
│ ├── SVM_horoscope.pkl # ✅ used
│ ├── RF_horoscope.pkl # ❌ not used
│ ├── NB_horoscope.pkl # ❌ not used
│ └── vectorizer.pkl
├── app.py
├── requirements.txt
└── README.md
🧚♀️ Author
Made with love and a sprinkle of delusion by Swati Upadhyay 💫