Aditya Dawn

Successfully crafted a multi-classifier pipeline predicting price fluctuations of commodities. Proactively wrote and tested prompts on LLM models (GPT, LLaMa, Gemini) using LangChain. Evaluated and analyzed diverse trading strategies to assist in optimization. Orchestrated a sophisticated cash-flow forecasting project for an NBFC client, achieving a 2.9% RMSE reduction. Developed global and local model explanation techniques using Shapley values and integrated counterfactual-based explanations. Developed a web scraping and NLP pipeline for sentiment analysis with 92% accuracy. Designed and deployed an in-house EDA platform for tabular and time series data.

Project Title: Renewable Energy Modelling. Conducted thorough data exploration with Data Visualization and Exploratory Data Analysis. Implemented advanced Regression-based-Time-Series Models for GHI predictive forecasting. Achieved an impressive R-squared score of 0.92 in the forecasting model.

Project Title: Environmental Sound Classification. Hands-on project using the ESC-50 dataset. Applied audio processing techniques for spectrogram extraction. Implemented Convolutional Neural Network (CNN) models for sound classification. Demonstrated consistent proficiency with an average accuracy score of 87%.