A H Brijesh

A modern, responsive, and animated portfolio website built with React and TailwindCSS. This project showcases my technical skills, professional experience, and personal projects in a visually appealing and interactive way. Featuring smooth scroll animations, clean design, and a contact form crafted to leave a lasting impression.

Committed to upholding the values of loyalty and truthfulness in every aspect of my professional journey. With unwavering integrity, I aspire to contribute my dedicated efforts and genuine sincerity to create a positive and trustworthy impact in any role I undertake.

The Sentence Emotion Predictor is a tool designed to analyze and predict the emotional tone of a given sentence. It employs natural language processing techniques to identify and classify the emotions expressed in text, providing valuable insights for applications such as sentiment analysis, customer feedback analysis, and emotion-aware chatbots.

A local Retrieval-Augmented Generation (RAG) system built for audit and transaction analysis. It allows users to query official audit manuals and receive accurate, context-grounded answers generated strictly from source documents.

An AI-powered chatbot designed to identify emotional distress and engage users in empathetic, human-like conversations. Built to support mental health, especially in critical situations, it uses an ensemble of Microsoft's DialoGPT and a custom Seq2Seq LSTM model.

The Student Success Predictor employs Naive Bayes to assess the likelihood of students achieving scores above 90, integrating study hours and personal factors. This model aids educators in identifying key elements influencing academic excellence, facilitating targeted interventions for enhanced student success. Contributions Welcome!!

Java Swing Calculator: Simple, user-friendly GUI calculator supporting basic arithmetic operations. Responsive design, real-time calculations. Contribute to enhance features and usability!

This Face Recognition System uses a Convolutional Neural Network (CNN) for classifying faces. It involves data preprocessing, model training, and prediction using a labeled image dataset. The trained model is saved in "model.keras" for future use, and the system includes a user interface for making predictions.

This is a full-stack food ordering application built using the MERN (MongoDB, Express, React, Node.js) stack. Users can browse menus, add items to their cart, and place orders. The application also features user authentication and an admin panel to manage menu items and orders.

IBM CAD Project: Utilized Linear Regression on IMD temperature data, SVM and Bagging on Pima Diabetes dataset, Random Forest on IBM DB2 data, and Multiple Regression on USA House Price data. Visualizations with Matplotlib.

Neural Network on MNIST Dataset: Implementation of a single-layer Neural Network using TensorFlow's Keras library. Train on MNIST, check predictions interactively with Drawingboard.py.

This Python script demonstrates a basic keylogger implementation using Tkinter for the graphical user interface and pynput for capturing keyboard events. It logs key presses, holds, and releases to both a text file (key_log.txt) and a JSON file (key_log.json).

This repository contains a Python notebook that demonstrates the use of the Mean Shift clustering algorithm for image segmentation. Mean Shift is a non-parametric clustering algorithm widely used in computer vision tasks.

Diabetes Prediction Project: Decision Tree Classifier implementation using Pima dataset. Explore data, visualizations, and contribute to enhance accuracy and interpretability. Contributions welcome!