Name: Aishwarya Hoysal K S
Type: User
Bio: π¨βπ» CSE Pre-Final Year Student | π Aspiring Data Science, AI, ML Enthusiast | π Exploring Evolving Technologies | π Lifelong Learner
Twitter: AH_2443
Location: Karnataka,India
Aishwarya Hoysal K S's Projects
The Bank Locker Management System efficiently handles locker rental, access, and maintenance. It tracks availability, assigns lockers, records contents, and monitors access securely, ensuring a seamless and secure experience for customers.
Bengaluru house price prediction serves as a valuable tool for individuals and businesses involved in the real estate market, helping them navigate the dynamic landscape and make well-informed decisions based on data-driven insights.
Exploring Git and GitHub fundamentals through Kunal Kushwaha's excellent tutorial. This comprehensive guide covers everything from basic concepts to practical project management, providing a solid foundation for version control and collaboration.
Email spam and ham classification employs machine learning to categorize incoming emails. By analyzing content, sender details, and patterns, it distinguishes between spam (unwanted) and ham (legitimate), bolstering email security and enhancing user experience.
Event scheduler is a web-based application widely used by event organizers and venues to manage events. An event scheduler helps the organizers easily create and update an event, track its progress, manage attendees, invite guests to the event, manage venues for events, and much more.
An Industrial NLP chatbot employs Natural Language Processing for tasks in manufacturing, logistics, or similar sectors. It aids in streamlining operations, managing inventory, providing real-time insights, and enhancing customer support, improving efficiency and productivity.
Iris classification refers to the task of categorizing iris flowers into different species based on their morphological characteristics. The most common dataset used for this classification task is the Iris dataset.
Use of AI and ML algorithms to assist in detection, analyzing large datasets of X-ray images to identify pneumonia markers with increasing accuracy.
Titanic classification predicts survival based on passenger data. Using machine learning algorithms, it analyzes features like age, gender, and class in a labeled dataset. The goal is to create a model that accurately classifies new data, reflecting the likelihood of survival in a Titanic-like scenario.