At AIVariant, I worked on machine learning and time series forecasting projects, including data preprocessing, exploratory data analysis, feature engineering, model development, and evaluation.
I built an Apple stock price prediction model using ARIMA, applying forecasting techniques to historical financial data.
For my diabetes prediction project, I developed and deployed a Python model using Logistic Regression that achieved 86% prediction accuracy. I integrated it with a Streamlit application for real-time predictions.
I also developed and evaluated CNN-based models, including VGG19 and ResNet50, for multi-disease classification using the ChestX-ray8 dataset.
