As a passionate data science and machine learning professional, I specialize in uncovering insights from complex datasets to drive strategic decision-making. With hands-on experience in predictive modeling, AI algorithms, and data visualization tools like Power BI and Tableau, I bridge the gap between data and actionable business intelligence. Currently pursuing an M.S. in Computer & Information Science (Data Science) at UNF, I am committed to leveraging technology to solve real-world problems through data-driven innovation.
0 + Projects completed
Aspiring Data Scientist with a strong foundation in data analysis, machine learning, and data visualization, eager to leverage skills to drive impactful business insight.
A start-up company using Zoho CRM with over 10K+ professionals globally.
Grade: A
Grade: 9.0
Below are the sample Data Analytics projects on SQL, Python, Power BI & ML.
This project performs text analysis and plagiarism detection on a collection of text documents. It leverages TF-IDF (Term Frequency-Inverse Document Frequency) for vectorizing the text data, and cosine similarity to detect potential plagiarism between documents. Additionally, it includes text classification using Logistic Regression and document clustering with K-Means.
The project leverages data from IPL matches to uncover insights and trends. It includes visualizations, statistical analysis, and potential predictive modeling.Data Analysis using Python Project
This project is focused on building a model for SMS spam detection. The primary goal is to classify SMS messages as either 'spam' or 'ham' (non-spam) using machine learning techniques. The implementation is designed for easy experimentation and understanding, making use of Jupyter Notebook and Python programming.
This project focuses on detecting fraudulent credit card transactions using machine learning techniques. The dataset used contains real-world credit card transactions labeled as fraudulent or legitimate. The implementation is designed to address class imbalance and optimize model performance.
This project involves analyzing Ethereum blockchain transaction data to gain insights into transaction trends, gas usage, failed transactions, and more. The dataset includes key attributes such as block numbers, timestamps, transaction values, gas usage, and whether the transaction was successful or failed.
Below are the details to reach out to me!
Jacksonville, Florida, USA