RITIKA Chouhan

I developed end-to-end image classification pipeline during my internship with Edunet Foundation. The project involved data preprocessing, augmentation, CNN/transfer learning models, evaluation (accuracy, precision, F1-score), and a prototype Flask API deployment. Achieved high accuracy (>90%) while ensuring model explainability using Grad-CAM. Gained strong hands-on experience in TensorFlow, Keras, PyTorch, OpenCV, and Scikit-learn, build production-ready ML solutions adaptable to real-world applications.

I conducted a detailed analysis of the agriculture sector, identifying key trends, challenges, and opportunities. Using Power BI, I designed interactive dashboards and visualizations that transformed complex datasets into clear, actionable insights. These insights enabled stakeholders to monitor performance, make data-driven decisions, optimize strategies, and plan for long-term improvements, demonstrating my ability to turn data into meaningful, decision-driving solutions.