Description : About the All AI ML Project's Here!
- Calories Burnt Prediction
- Car Re-sale value prediction
- Credit Card Fraud Detection
- Diabets Prediction
- Predicting Fuel Efficiency
- Rock or Mine
- Spam detection
- Wine quality
Description: redict the number of calories burnt during physical activities based on features like duration, heart rate, weight, and type of activity. This project helps users track fitness progress and plan workouts effectively. Status: ✅ Completed
Description: Predict the resale value of cars based on features such as age, mileage, brand, model, and fuel type. This project helps car owners and dealerships estimate a fair resale price. Status: ✅ Completed
Description: Detect fraudulent credit card transactions using machine learning algorithms. This project helps financial institutions identify and prevent fraudulent activities in real time. Status: ✅ Completed
**Description:**Predict the likelihood of a person having diabetes based on medical features such as glucose level, blood pressure, BMI, age, and insulin. This project helps in early detection and preventive healthcare. Status: ✅ Completed
Description: Predict the fuel efficiency (miles per gallon) of vehicles based on features such as engine size, cylinders, horsepower, and weight. This project helps in analyzing vehicle performance and environmental impact. Status: ✅ Completed
Description: Classify objects as rock or mine based on sensor measurements. This project is a classic classification problem useful in geoscience and defense applications. Status: ✅ Completed
Description: Detect whether emails or messages are spam or not using machine learning and NLP techniques. This project helps in filtering unwanted communications. Status: ✅ Completed
- Python 🐍
- Pandas & NumPy 📊
- Matplotlib & Seaborn 📈
- Scikit-learn 🤖
- TensorFlow / Keras ⚡
- Jupyter Notebook 📓
- Clone the repository:
git clone https://github.com/your-username/your-repo-name.git- Navigate into the project folder:
cd your-repo-name
- Install dependencies:
pip install -r requirements.txt
- Open the project notebook in Jupyter Notebook and run the cells.