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About Me

I'm a Computing and Data Science sophomore at Sai University with experience in Docker, Kubernetes, Microservices, Java, Python, and Apache Kafka. I'm interested in Machine Learning and pursuing a career in research.

Skills

Docker Kubernetes Java Python Apache Kafka Git NumPy Pandas Matplotlib Seaborn scikit-learn SQL Neo4j

Contact Me

LinkedIn Email

Feel free to reach out if you'd like to connect or collaborate on projects related to software engineering or machine learning!

Vidhyakshaya Kannan's Projects

california-house-price-prediction icon california-house-price-prediction

This project analyzes features like median income, total rooms, and population to predict median house values in California. The project involves data preprocessing, exploratory analysis, and training Linear Regression and Random Forest models.

campusher icon campusher

CampusHER is a mobile application designed to provide university women with access to health resources, appointment scheduling, health tips, and more. The backend is developed using Python with Flask (or Django), and the frontend is built using React Native.

cognitive-neuroscience-research icon cognitive-neuroscience-research

Python-based simulations for cognitive neuroscience experiments using OpenSesame. Synthesised audio stimuli using PyAudio to support Dr. Jamshed Bharucha's research endeavors investigating the impact of music on human brain function.

diabetes-prediction-using-support-vector-machines icon diabetes-prediction-using-support-vector-machines

Web application for predicting diabetes based on medical information. Utilizes SVM model trained on a dataset of diabetes patients to make predictions. Provides user-friendly interface for individuals to assess their risk of diabetes based on their medical data.

nhanes-age-prediction icon nhanes-age-prediction

This project utilizes the National Health and Nutrition Examination Survey (NHANES) dataset to classify individuals into age groups based on various health and lifestyle features. The primary goal is to predict whether a respondent is an adult (under 65 years old) or a senior (65 years and older).

sec-10k-summarizer icon sec-10k-summarizer

Web application that allows users to summarize sections of SEC filings using AI-powered text summarization. Users can input the URL of the SEC filing and select the section they want to summarize. The application then extracts the text from the specified section, cleans it, and generates a concise summary using Google's PaLM API.

space-invaders icon space-invaders

Used the pygame module available in Python to develop an engaging game which involved multiple game development fundamentals such as creating a game window, adding images and employing movement mechanics, detecting keyboard inputs and collisions and adding sounds and background music.

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