Within the MERN stack, I intricately weave MongoDB, Express.js, React.js, and Node.js to sculpt immersive digital experiences that empower organizations to thrive in the dynamic landscape of the digital world.
Hey, Everyone! I'm Sahithya, an ambitious Software Engineer with a dedication to software Development. Currently, I am pursuing a graduate degree (Master of Science) in Computer Science at University Of Illinois. This pursuit reflects my unwavering passion for coding, insights and a commitment to continuous learning. I am eager to leverage my skills and education to contribute meaningfully to the field of Software Engineering.
Anomaly event detection using machine learning algorithms automatically identifies unusual patterns in data. This process involves data collection, preprocessing, model training, anomaly detection, and alerting. It helps organizations identify threats, improve efficiency, and reduce the risk of loss and damage.Implemented machine learning algorithms to automatically detect anomalies in data, resulting in an 80% reduction in fraud incidents and improving overall data integrity and security.
The school proctor web application is a comprehensive platform designed to streamline the management of student results and attendance. It provides an intuitive interface for educators to effortlessly record and track student performance, monitor attendance patterns, and generate insightful reports. With features such as automated grading, attendance tracking, and data visualization, this application empowers schools to maintain accurate and up-to-date records, ensuring a seamless flow of information between teachers, administrators, and parents. By leveraging this powerful tool, educational institutions can enhance their operational efficiency, promote data-driven decision-making, and ultimately foster a conducive learning environment for students to thrive.
The prototype is an online retail platform specifically designed for grocery chains dealing in products like cookies, chips, and other similar items. It aims to provide a seamless and convenient shopping experience for customers, allowing them to browse and purchase a wide range of grocery items from the comfort of their homes or on the go. With an intuitive user interface and robust inventory management system, the platform enables customers to easily navigate through product categories, view detailed product information, and place orders. Additionally, features such as secure payment gateways, order tracking, and delivery options ensure a hassle-free transaction process, catering to the evolving demands of modern consumers in the grocery retail sector.
Utilizing pandas, nltk, sklearn, and re libraries, a recommendation engine was implemented for the IMDB Movies Dataset. This engine leverages natural language processing techniques to analyze movie descriptions and metadata, enabling it to provide personalized movie recommendations based on user preferences and similarities within the dataset. By employing machine learning algorithms from sklearn, the engine can identify patterns and extract relevant features from movie titles, genres, and plot summaries. The recommendation system offers a seamless and tailored experience for users, suggesting movies aligned with their tastes and interests, enhancing their movie-watching journey.
Chicago, Illinois