I am an early-career data professional with a strong foundation in M.Sc. Computer Science (Data Analytics). I specialize in transforming raw data into actionable insights and building practical AI/ML solutions. My focus involves cleaning complex datasets, building predictive models, and exploring Generative AI applications using Python and Cloud tools.
Predicting future values in sequential data to assist in trend analysis.
Implemented an LSTM neural network utilizing windowing techniques for data preparation and normalization.
Successfully compared the deep learning model against baseline statistical approaches, evaluating performance using RMSE and MAE metrics used for time-series validation.
Analyzing facial images to classify demographic attributes and emotional states.
Built a Convolutional Neural Network (CNN) with data augmentation to handle class imbalance. Integrated OpenCV for image processing.
Gained deep understanding of bias in datasets and ethical considerations in facial recognition technology.
Bridging the communication gap for sign language users through real-time recognition.
Collected gesture data to train an SVM classifier for static signs. Integrated Gemini API to convert recognized signs into natural text and audio.
Created a hybrid system combining traditional ML (SVM) with modern GenAI capabilities for enhanced accessibility.
Managing large volumes of email efficiently using natural language queries.
Built a Retrieval-Augmented Generation (RAG) pipeline. Cleaned Gmail data, created vector embeddings, and used LangChain for semantic search and response generation.
Enabled rule-based categorization and context-aware responses, streamlining email management.
I am currently open to opportunities in Data Analytics, Data Science, and AI/ML. Send me a message using the form below.
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