yadavnikhilrao,Nikhil Kumar,yadavnikhilrao,github

About Me:

👋 Hello! I'm student pursuing my Master's in Computer Applications (MCA) at KIEt Group of Institutions in Delhi-NCR.
💡 Some technologies I enjoy working with include Python, Machine Learning, Deep Learning, NLP, MySQL, HTML, CSS, C.
🌱 I'm on track for learning more about Data Structures and Algorithm, Software Development, Artificial Intelligence.
✉️ Get in touch with me via email at [email protected] or connect on LinkedIn.
💬 Ask me about Data Science, Artificial Intelligence

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Nikhil Kumar's Projects

breast-cancer-detection-using-machine-learning

Compared different machine learning techniques across different performance measures. Achieved an accuracy of 98.2%.

food-recommendation-system

This is a machine learning web app, which when executed, the client gets to choose a food item based on his own liking, and we recommend 10 more such similar foods through our recommendation system.

insightfulequity

InsightfulEquity empowers investors with actionable insights, predictive analytics, and sentiment analysis for informed investment decisions. Using data analysis, machine learning, and NLP, we decode financial markets. #Finance #DataAnalysis #InvestmentInsights

movie-recommendation-system-v-1

A movie recommendation system is an ML based approach for filtering or predicting user's movie preferences. This system uses user's past choices and details that they provide.

patient-management-system-or-pranik-medical-services-pms

PMS (Patient Management System) is a comprehensive healthcare solution developed to streamline patient care and management. This project aims to enhance operational efficiency, improve communication, and simplify administrative tasks for healthcare providers.

the-ultimate-movies-recommendation-system-v-2-pranik-movies

Pranik Movies is a user-friendly web application designed to help you search and discover your favorite movies. With a vast database of movies, you can easily find information about different films, watch trailers, and get details such as release date, cast, and ratings.