Karthik Reddipalli

Developed a web-based application for the detection and classification of kidney diseases using Convolutional Neural Networks (CNN) and InceptionV3.

Contributed to a 'Fake News Detection' project, utilizing Python and Google Colab to analyze the reliability of news information using a dataset of fake and real news.

Worked on prompts and AI tools, gaining extensive knowledge in Generative AI and Prompt Engineering. Trained in creating essential prompts for AI applications and familiarized with industry tools like ChatGPT and Gemini.

Created a web-based application for detecting DDOS attacks, employing algorithms like Random Forest, Logistic Regression, and Support Vector Machine to maximize accuracy.

Developed a web-based application to identify and analyze dental fluorosis severity using CNN and YOLO as part of a community service project.

Designed a mobile recharge system and a project management system for musicians using Java and RDBMS, focusing on backend and UI design.

Activities and societies: Relevant coursework includes Data Science, AI and Machine Learning, Database Management, and more.

Pursuing a Bachelor of Technology in Artificial Intelligence and Data Science, focusing on various aspects of AI and data science including programming languages, data structures, and machine learning.

Completed MPC with a focus on Mathematics, Physics, and Chemistry, laying a strong foundation for engineering studies.

Completed schooling with a focus on foundational education, preparing for higher studies.