I build high-performance Machine Learning models and implement advanced algorithms (Random Forest, Neural Networks, Clustering) to solve complex problems.
With a strong foundation in Python, R, and Big Data frameworks like Hadoop & Spark, I transform raw data into strategic solutions, ready to innovate on a global scale.
A selection of my recent work in Machine Learning, Deep Learning, and Data Science.
Exploring CLIP's performance in zero-shot image-text classification for livestock.
Comparing FastText, Transformer, and LSTM using GloVe embeddings on AGNews.
Predicts weekly sales using XGBoost. Deployed as an interactive Streamlit dashboard.
Analyzed market trends using Python, Spark, and Hadoop to identify patterns.
Applying K-Means clustering to identify distinct customer groups for marketing.
Predicting herbal compound activity for breast cancer therapy using ML.
Simulating Meta Inc. stock price trajectory using stochastic modeling.
Time-series volatility modeling for climate data analysis (Temperature & CO2).
Data analytics for predicting and analyzing global EV sales trends (2010-2024).
Analyzing global renewable energy adoption trends using Looker Studio.
System to automate file backup and monitor security across servers.