Sai Sankeerth

E-Commerce Website

E-commerce website with Python, PostgreSQL, SQLAlchemy, and Django frameworks. 

• Developed and deployed an e-commerce website with PostgreSQL, SQLAlchemy, and Django. Implemented RESTful APIs, user authentication, payment integration, and optimized database queries for improved performance.  

• Improved PostgreSQL database performance by implementing indexing and query optimization techniques, resulting in reduced query response times and improved system efficiency.

• Enhanced the user experience by implementing a responsive and intuitive user interface design, making the e-commerce website more user-friendly and accessible across various devices.

House Price Prediction Using Machine Learning

In this project, the application will allow users to input specific parameters, such as location, built-up area, specifications, amenities, etc., and the algorithm will calculate the predicted price of the house by utilizing techniques like Multiple Linear Regression (MLR) and Support Vector Regression (SVM).

• preprocessed the datasets from Kaggle by refining them, eliminating redundancies, and correcting inaccuracies in the data.

• Achieved outstanding predictive accuracy, with the MLR model achieving an impressive accuracy rate of 96% and the SVM model attaining 92% accuracy. 

Keylogger_Cryptography

Keyloggers, although originally designed for legitimate purposes such as monitoring computer usage or assisting with troubleshooting, have indeed gained notoriety due to their potential for misuse. 

• Efficiently records keystrokes and stores them in a file named "keylogger.txt." Developed a keylogger with original intentions for legitimate purposes. Acknowledged the potential for misuse that keyloggers have gained notoriety for.

• Designed for easy retrieval and analysis of recorded keystrokes.

• Emphasized the importance of recognizing ethical considerations when using keyloggers.