Name: Balaji M P
Type: User
Company: Queen Mary University of London
Bio: Master's Student in Big Data Science seeking Internships, Part-Time roles in Data Science and Data Engineering | Ex-@Accenture, Ernst & Young
Location: London, United Kingdom
Blog: https://www.linkedin.com/in/balaji-mp/
Balaji M P's Projects
The project aims to analyze and compare key performance indicators of a major telecommunications provider using Tableau
End to End machine learning project on regression using cloud based deployment
An image classification project implementing a custom neural network architecture using PyTorch to accurately classify images from the CIFAR-10 dataset
[JBHI' 24] Neural Networks based Smart e-Health Application for the Prediction of Tuberculosis using Serverless Computing
This project aims to build machine learning pipelines for two tasks: accurately classifying images as rice or chips and determining if a dish is from Indian cuisine.
This project involves the implementation of Market Basket Analysis, a powerful technique in retail analytics.
Web-based application that allows users analyze their food intake to obtain nutrition info of their diet. The application follows a client-server architecture with the front-end serving as a user interface and the back-end providing a RESTful service interface for CRUD operations.
This GitHub repository showcases my hands-on exploration of salary data dependencies, the interaction between education and occupation, and a comprehensive Principal Component Analysis (PCA) on college information, providing insights and practical implications in a simplified manner.
This project involves the implementation of RFM (Recency, Frequency, Monetary) analysis, a powerful technique in customer segmentation and targeting
End to End machine learning project on classification using cloud based deployment
Azure Data SQL Samples - Official Microsoft GitHub Repository containing code samples for SQL Server, Azure SQL, Azure Synapse, and Azure SQL Edge
In this project, we leverage time series forecasting techniques to make educated estimates of wine sales throughout the 20th century.
This is a submission for problem statement given by The Machine Learning Company for their fellowship program. This involved solving the problem statement with NLP techniques.