This project demonstrates the integration of Agentic AI with SQLite, creating an intelligent assistant that interacts with the Chinook database. It leverages advanced AI capabilities to execute nat…

This project is an interactive CSV data analysis tool powered by Crew AI, enabling users to extract insights and answer detailed queries from CSV files using advanced LLMs. It integrates Google, Gr…

This project demonstrates a Retrieval-Augmented Generation (RAG) system powered by a PgVector vector database and phidata. It leverages AI agents for interactive knowledge retrieval and querying fr…

A multi-agent AI system leveraging Agno's framework to integrate web search and financial analysis tools, offering interactive insights via a user-friendly GUI-based Playground App.

In this project, we built a real-time object detection and tracking system using YOLOv12, leveraging the COCO dataset for its diverse object classes. It combines state-of-the-art detection accuracy…

This project uses LangChain agents and Google Generative AI to build a RAG system, combining LLMs with tools like Wikipedia, Arxiv, and custom retrievers for accurate, real-time answers.

In this project, we developed a Streamlit app that uses Groq API and Google Generative AI for question-answering by embedding and retrieving content from multiple PDFs. The app leverages prompt eng…

In this project, we implement a Retrieval-Augmented Generation (RAG) system using the Groq API. The application dynamically retrieves and processes context from documents, enabling accurate and con…

This project is a PDF Question Answering App that enables users to upload any PDF and ask questions about its content. Using a retriever-augmented generation (RAG) approach, it efficiently retrieve…

In this project, users can input any URL and ask a question related to its content. Using Retrieval-Augmented Generation (RAG) and LangChain, the app retrieves the most relevant answer from the web…

This project showcases how Retrieval-Augmented Generation (RAG) can be applied to create an efficient and user-friendly system for querying large text documents. With this approach, users can easil…

In this project, we built an AI-powered Applicant Tracking System (ATS) using Google Generative AI to analyze resumes and match them with job descriptions, providing detailed evaluations and compat…

This project uses LLMs and AI to transform YouTube transcripts into concise, detailed notes. Simply input a video link to quickly grasp key points without watching the entire video.

In this project, the AI-Powered Calorie Analyzer uses a large language model (LLM) to analyze meal images and provide accurate calorie counts, nutritional insights, and personalized health suggesti…

In this project, we use Google Gemini to automatically extract key information from uploaded invoice images. Users can ask specific questions, and the app generates responses based on the extracted…

This project leverages Google's Gemini LLM to analyze uploaded images and generate detailed descriptions or insights based on user prompts. It combines advanced AI capabilities with Streamlit for …

This project is an interactive Q&A chatbot built using Google's Gemini Pro LLM. Users can input questions, receive real-time responses, and view the complete chat history.

Interactive Text Generator Using LLM is a Streamlit-based app powered by Google's Gemini LLM. Users can input questions and receive AI-generated responses instantly. This project showcases how LLMs…

This project demonstrates active learning for text classification using the Small-Text library on the IMDB dataset. A logistic regression model is trained iteratively, selecting the most uncertain…

I applied active learning to the IMDB dataset for sentiment analysis. Starting with a small labeled subset, I trained a model and used uncertainty sampling to select and label challenging reviews. …

This project explores active learning techniques, focusing on query strategies to optimize informative data selection for model training. It aims to reduce labeled data while improving model perfor…

This project explores the implementation of active learning techniques, focusing on various query strategies to optimize the selection of informative data points for model training. It aims to redu…

An AI-driven system leveraging real-time face recognition to automate attendance, ensuring accuracy, scalability, and seamless CSV logging of names and timestamps.

This project implements a real-time face recognition system using Python, OpenCV, and the face_recognition library. It identifies individuals by comparing facial features from live video streams wi…

This project applies neural style transfer to create new images by merging the content of one image with the artistic style of another.

I used VAE and CVAE in this project to generate images based on user input.

This project integrates Autoencoders, PCA, and CNNs for efficient image processing, combining dimensionality reduction, denoising, and enhanced feature extraction for image analysis and compression.

This code showcases text preprocessing (tokenization, stopword removal, and standardization), training a Word2Vec model to generate word embeddings, and analyzing word relationships using metrics l…

This project demonstrates Principal Component Analysis (PCA) from scratch for grayscale images, colored images, and the Olivetti Faces dataset. It involves steps like mean centering, covariance mat…