Meesala Nithin

Diabetes Prediction Model Using Machine Learning:                        OCT 23 -  DEC 23

• Developed a machine learning model that predicts whether the patient is affected by type 2 diabetes or not.
• Model is built using machine learning models like KNN, SVM, Logistic Regression, Random Forest, Decision Trees, and C4.5.

Amazon Clone:                                                                                       JUN 23  - JUL 23

• Created a fully responsive layout utilizing CSS's grid system and media queries, ensuring seamless usability across a variety of screen size.
• I recreated the Amazon home page design, including the header, navigation, products section, and footer, achieving a higher degree of visual accuracy.
• Front end designed using Flask, Html, CSS. Backend: Python. Model performance is evaluated by accuracy, the Roc curve, and the confusion matrix.

Todo List Web App :                                                                              AUG 23 -SEP 23 

• Developed a web-based Todo List application using node.js where the user can mark daily activities and tasks. Responsive for all screen sizes with simple and precise styling. Upon completion, tasks can be marked as completed.
• The tasks are stored in postgres sql database and tasks are available at all time.
• Tech Stack: Node.js, Express.js, EJS, JavaScript, HTML, CSS.

• Wipro Talent_Next Java Certification
• Python Certification
• GDSC Web-Development Co-Leader