Crop Yield Prediction using ML

Developed a computer model that can estimate future crop yields by analyzing historical data on weather conditions, soil properties, planting practices, and past yields, using machine learning algorithms to identify patterns and relationships between these factors, allowing farmers to make informed decisions about crop selection, resource allocation, and potential risks to optimize their harvest outcomes.

Tools used are Data collection & analysis tools, Machine Learning algorithms, Neural Networks, Python

Battery Management System in Electric vehicles

Developed a model of sophisticated electronic system that monitors and controls the battery pack within an EV, ensuring its safe and efficient operation by preventing over charging, over discharging, over heating, and maintaining optimal cell balancing, ultimately extending the battery life and vehicle performance