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      MY PROJECTS

Explore my data science and machine learning projects, where I unravel insights and solve real-world challenges through the power of data. 

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Exploratory Data Analysis on CHD Dataset 

In this exploratory data analysis (EDA), I delved into a dataset sourced from Kaggle, which is focused on understanding the risk factors associated with coronary heart disease (CHD). Recognizing and forecasting CHD risk is crucial in public health, as it enables early intervention and minimizes morbidity and mortality. By analyzing this dataset, I aimed to shed light on the complex relationships between factors such as smoking habits, health variables, and CHD risk, particularly emphasizing the impact of smoking on cardiovascular health. 

Fashion MNIST

In this collaborative project, I worked alongside two team members to develop a clothing classification system using the FashionMNIST dataset. We aimed to create a robust classifier that can identify different types of clothing items with high accuracy. We designed and executed training and validation strategies, aiming to achieve the highest accuracy in classifying clothing items. Our efforts encompassed various aspects of machine learning, data preprocessing, model architecture, and hyperparameter tuning.

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TD Hospital Exploration 

TD-Hospital-Exploration is a data-driven project designed to uncover vital patient survival factors and bolster decision transparency at TD Hospital. Through meticulous analysis of extensive structured patient data and advanced machine learning techniques, we strive to offer actionable insights. 

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 TAMU Datathon 2o23 

Tamu Datathon Marky Challenge
(2nd Place) 

MarkyChallenge is a data science project developed for Tamu Datathon, focusing on predicting user approval of AI-generated content. By analyzing both textual and visual data, our project leverages machine learning techniques to provide valuable insights into user preferences, offering potential enhancements to content creation and recommendations

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TAMU Datathon 2o23 

DATABASE INTERACTION USING AUTOMATIC SPEECH RECOGNITION

Constructed a multilingual database system enabling users to interact in their native language. Used Automatic Speech Recognition for spoken-to-text conversion and Natural Language Processing (NLP) to perform lexical, syntactic, semantic, and pragmatic analysi

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