SRU Canteen

SRU Canteen offers a variety of hygienic and affordable food options, catering to the tastes of students and staff alike. With its clean environment and quick service, it provides a welcoming space for meals and refreshments on campus.

Technology Stack:

HTML,CSS

Full-Stack

Company Employee Details

Company employee details typically include essential information such as names, job titles, departments, and contact details. This data is crucial for streamlining internal communication, managing responsibilities, and supporting HR operations like payroll and performance evaluations

Technology Stack:

C programming Language

Dev c++

Insurance Claim Fraud Detection

Insurance Claim Fraud Detection involves using data analytics and machine learning techniques to identify fraudulent claims. By analyzing patterns, anomalies, and behaviors, this process helps insurance companies mitigate risks and reduce financial losses.

Technology Stack:

Python

Google Colob

Machine Learning

Cricket Macth Analytics using PowerBI

Developed an interactive dashboard to analyze player performance, team statistics, and match outcomes. Leveraged Power BI to visualize runs, wickets, strike rates, and match trends. Enabled data-driven insights for strategic decision-making and fan engagement.

Technology Stack:

statistics

PowerBI

dashboard

House Price Prediction using Machine Learning

Built a machine learning model to predict house prices based on features like location, size, and number of rooms. Used regression algorithms and feature engineering to improve accuracy. Visualized predictions and insights to support real estate decision-making.

Technology Stack:

Python

Google Colob

Machine Learning

Diabetic Retinopathy Detection

Developed a deep learning model using CNNs to detect diabetic retinopathy from retinal fundus images. Preprocessed images and trained the model for multi-stage classification (No DR, Mild, Moderate, Severe, Proliferative DR). Aimed to assist early diagnosis and prevent vision loss through automated screening.

Technology Stack:

Python

CNN

Machine Learning

Netflix Titles Data Analysis using Python

Performed exploratory data analysis on the Netflix dataset using Python libraries like Pandas, Matplotlib, and Seaborn. Analyzed trends in content type, genre, country distribution, and release year. Gained insights into viewing patterns and content strategies to understand platform growth.

Technology Stack:

Python

seaborn

Matplotlib

Rice Image Classification using CNN

Built a Convolutional Neural Network (CNN) to classify rice grain images into five distinct varieties. Preprocessed the dataset with normalization and augmentation to improve model performance. Achieved high accuracy in predicting rice types, aiding in agricultural quality control and automation.

Technology Stack:

Python

CNN

Deep Learning

Gender Vocie Prediction

Developed a machine learning model to predict gender based on voice characteristics using acoustic features like pitch, frequency, and MFCCs. Applied algorithms such as SVM and Random Forest for classification. Aimed to enhance voice-based applications in security, personalization, and speech analytics.

Technology Stack:

Python

LSTM

MFCC