-
Master’s student in Data Science at the University of Texas at Arlington
-
Passionate about applying machine learning, NLP, and predictive analytics to solve real-world problems
-
Building hands-on projects in sentiment analysis, disaster prediction, and computer vision
-
Confident in working with real-world datasets and continuously learning to grow as a Data Scientist
-
Machine learning model development and evaluation
-
Natural Language Processing (sentiment analysis, transformers, text classification)
-
Predictive analytics and time series forecasting
-
Deep learning projects in image recognition and classification
-
Data visualization and storytelling with BI tools
-
Twitter Sentiment Analysis – Compared classical ML (TF-IDF + Logistic Regression) with BERT, achieving 92% accuracy; deployed a demo with Gradio
-
Disaster Risk Prediction – Built an ML pipeline using XGBoost, SMOTE, and SARIMA forecasting, visualized on an interactive map
-
Deepfake Image Detection – Designed a classifier to detect real vs fake images across multiple categories
-
Healthcare Workforce Analysis – Conducted survey research and generated insights from national-level data
-
Reinforcement Learning Experiments – Implemented Q-Learning, Policy Iteration, and Deep Q-Learning on custom environments
-
Programming: Python, SQL
-
Machine Learning: scikit-learn, XGBoost
-
Deep Learning: PyTorch, TensorFlow, Hugging Face
-
NLP: NLTK, spaCy, gensim
-
Visualization: matplotlib, seaborn, plotly, Tableau, Power BI
-
Tools: Git, Jupyter, Streamlit, Flask, VS Code, Google Colab
LinkedIn: linkedin.com/in/smrithichembath