Poojapriya Nagaraj

Hardworking and passionate job seeker with strong organizational skills eager to secure entry-level position. Ready to help team achieve company goals.

• Heart Attack Analysis & Prediction Using Supervised Machine
Learning
Led the "Heart Disease Prediction" project, utilizing machine learning
to enhance early detection and management of heart disease. Through
exploratory data analysis and the deployment of models like Decision
Trees, SVM (91.80% accuracy), KNN, and Logistic Regression, I achieved
notable predictive accuracy. SVM was identified as the superior model
for its precision and potential clinical application. This initiative marks
a significant step towards integrating AI in healthcare for personalized
medicine and efficient resource allocation in combating heart disease.

• 450 Birds Species classification with CNN
Led a deep learning project for classifying 450 bird species, utilizing
TensorFlow and transfer learning with a VGG16 model. Achieved 93%
accuracy on a challenging Kaggle dataset, demonstrating expertise in
CNNs and efficient data handling.

• Image Clustering
Executed a sophisticated image clustering project to identify patterns
and categorize unlabelled image data. Applied state-of-the-art
unsupervised learning algorithms to dissect complex datasets,
revealing intrinsic groupings and insights. Pioneered data-driven
strategies to refine image analysis and mining, significantly enhancing
pattern recognition and data categorization processes.

• Chat-bot application
Crafted an NLP-driven chatbot offering precise legal guidance on
divorce, leveraging text mining and AI to distill and categorize complex
data. Utilized Naive Bayesian and Nearest Neighbor algorithms for
accuracy, enhancing accessibility to legal support.

Apple Developer Academy