About Me
I am a versatile Data Scientist with a strong foundation across the full data science lifecycle, including data collection, cleaning, exploration, modeling, visualization, and deployment of insights. I use Python extensively for data manipulation, statistical analysis, and machine learning, applying libraries such as Pandas, NumPy, Scikit learn, and Matplotlib. I work confidently with SQL to extract, join, validate, and optimize data from relational databases while applying exploratory data analysis techniques to uncover trends, patterns, and anomalies. I design, train, and evaluate machine learning models for prediction and classification, focusing on accuracy, reliability, and interpretability. I am proficient in Tableau and other visualization tools to build interactive dashboards and clear data stories that support decision making. I also have working knowledge of HTML, enabling effective presentation of data driven insights on web platforms.
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