Data-driven and curious machine learning enthusiast with a passion for building intelligent, real-world solutions. Aspiring to deepen expertise in machine learning, data visualization, SQL, and Python to develop impactfu…
Data-driven and curious machine learning enthusiast with a passion for building intelligent, real-world solutions. Aspiring to deepen expertise in machine learning, data visualization, SQL, and Python to develop impactful models and tools that enhance decision-making, optimize processes, and drive AI powered innovation
Built and evaluated ML models (Logistic Regression, Random Forest) to predict autism risk from behavioural and demographic data • Pre-processed data with missing value handling, feature scaling, and categorical encoding • Achieved ~88% accuracy through model tuning and experimentation • Developed a secure Flask web app with authentication and structured data collection • Displayed predictions with confidence scores, following ethical AI and medical-disclaimer practices
• Performed exploratory data analysis (EDA) on the Netflix dataset to identify trends in movies and TV shows across countries, genres, and release years. • Cleaned, transformed, and prepared data for deeper analysis and pattern identification. • Created visualizations using Matplotlib and Seaborn to highlight content distribution and audience insights. • Delivered actionable insights through charts and dashboards to support data-driven decision-making.
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