1. Predicting The Price of Used Cars
- Developed an effective machine learning model utilizing datasets to predict used car prices. Technologies used include Python, Scikit-learn, regression algorithms.
Tools: Jupyter Notebooks, Pandas, NumPy.
2. Solar Power Prediction
- Created a predictive model using time series analysis and machine learning algorithms. Technologies include Python, Scikit-learn, time series forecasting methods. Implemented visualizations to display solar power production timelines. The model has the capability to forecast variations in the next six months or coming years.
Tools: Jupyter Notebooks, Matplotlib, Seaborn.
3. Rice Leaf Disease Prediction
- Developed an effective deep learning model utilizing Convolutional Neural Networks (CNN) and ResNet50. Trained on diverse diseased images sourced online. The model automatically recognizes and detects diseases, showcasing expertise in image classification and deep learning.
Tools: Python, TensorFlow, Keras, Jupyter Notebooks.
4. Heartbeat and Temperature Monitoring System
- Integrated Arduino with temperature and pulse sensors to create a comprehensive monitoring system. Leveraged Arduino programming for interfacing and data collection. Demonstrated proficiency in hardware interfacing and real-time data acquisition.
Tools: Arduino IDE, Pulse Sensor Library.
5. Frontend Project: Crypto Currency Tracker
- Developed a responsive web application using HTML, CSS, and React.js. Utilized Axios to fetch live APIs from Cryptonator, showcasing proficiency in web development and API integration. The app provides real-time tracking of cryptocurrency prices, volume, and changes, demonstrating skills in frontend development and data visualization.
Tools: Visual Studio Code, React Developer Tools.