Arjun Sagar's repositories
Applied-Linear-Algebra
This repository contains a dataset comprising real-life performance data of new employees, encompassing demographic information and test scores. The dataset serves as a fundamental resource for machine learning assignments within the context of the Applied linear Algebra for Machine learning course.
CS310---DBMS-Class-Hackathon
The challenge was to design a database for a Swimming Pool management system, focusing on managing swim class enrollees. It required students to create both a Conceptual and Physical Data Model based on provided schemas.
DBMS-VEHICLE-INSURANCE
This repository contains the solution for DBMS Course Project, focusing on designing a database model tailored for a Vehicle Insurance Company. It offers students practical exposure to data modeling, normalization techniques, relational database design, and SQL query implementation.
Dimensionality-Reduction-in-Oncology-
This project involves the application of dimensionality reduction techniques i.e., Principal Component Analysis (PCA), on a cancer patients dataset. The goal is to simplify the dataset by reducing its dimensionality, making it easier to visualize and analyze, while retaining essential information.
Federated-learning-over-IOMT
This project implements federated learning using a ResNet-34 model to classify chest X-ray images into various medical conditions. By distributing the training process across multiple clients holding local datasets, the approach ensures data privacy and leverages the power of decentralized learning.
FOOTBALL_DATASET
This dataset is employed for a detailed case study on football player statistics. It encompasses diverse attributes such as player ID, nationality, squad, birth year, value, height, position, preferred foot, league, and more
Hand-gesture-recognition-using-Machine-learning-techniques
This is an innovative project on hand gesture recognition using machine learning techniques to control media playback functions. The project utilizes the MediaPipe framework for real-time hand detection and tracking, along with pyautogui and pycaw libraries for controlling keyboard, mouse, and audio functions. They provide Real-Time Processing.
Image-classification-model
This repository hosts code for a deep learning project focused on classifying chest X-ray images into normal and abnormal categories, with a specific emphasis on detecting COVID-19 and pneumonia cases. Leveraging convolutional neural networks (CNNs) and transfer learning methodologies, the project aims to achieve precise classification outcomes.
Intrusion-Detection-System
This project uses XGBoost for intrusion detection in cloud computing, achieving 99.17% accuracy on the KDDcup99 dataset. Leveraging AWS services like Amazon S3 and SageMaker, we ensure robust security and efficiency in handling large datasets.
Meta-Analysis-on-Impact-of-Maternal-Nutrition-on-Low-Birth-Weight-in-Developing-Countries
This repository highlights the significant associations between maternal nutrition interventions (such as iron and folic acid supplementation, maternal hemoglobin levels,& dietary diversity score) and the likelihood of low birth weight (LBW) in developing nations. The analysis reveals varying effect sizes and degrees of heterogeneity among studies.
Object-oriented-programming-LabAssignments
This repository contains a series of lab assignments focusing on object-oriented programming (OOP) concepts implemented in Python. Each assignment is designed to reinforce fundamental OOP principles and techniques through practical exercises and projects.
Object-oriented-programming-using-python--hackathon
During the hackathon, a backend application was created in Python to collect user input and store it in CSV files. There was no frontend development involved, as the focus was solely on Python programming to ensure accurate data storage.
Python-practice
This repository is dedicated to Python practice, featuring a collection of scripts covering fundamental Python concepts. From basic syntax to control structures and data types, these scripts are designed to help users improve their Python skills.
Sequence-to-sequence-networks-for-multi-text-document-summarization
This repository explores the use of advanced sequence-to-sequence networks and transformer models, such as BERT, BART, PEGASUS, and T5, for summarizing multi-text documents in the medical domain. It leverages extensive datasets like CORD-19 and a Biomedical Abstracts dataset from Hugging Face to fine-tune these models.
STATISTICS-UNIT.04
This analysis is part of our comprehensive statistics course project. This chapter encompasses critical topics such as goodness of fit., test for independence, and contingency tables with Yates correction. These concepts are essential for examining data relationships and validating statistical models.