SreeEswaran

Build-RAG-Agent-with-LLM

This repository contains the implementation of a Retrieval-Augmented Generation (RAG) agent using Large Language Models (LLMs). RAG agents combine the power of information retrieval with text generation, enabling applications such as intelligent question-answering systems, and more.

Image-Captioning-Transformer

This project demonstrates an image captioning model using a Transformer architecture. The model takes an image as input and generates a descriptive caption. We use the COCO dataset for training and evaluation.

Image-classification-using-CNN

This project demonstrates image classification using a Convolutional Neural Network (CNN) on the CIFAR-10 dataset. The model is trained to classify images into one of 10 classes.

Image-Classification-using-EfficientNet

This project uses a pre-trained EfficientNet model to classify images into different categories. The model is fine-tuned on a custom dataset for this purpose.

KAN-based-Movie-Review-Sentiment-Analysis

This project showcases the implementation of a Knowledge-Aware Neural Network (KAN) for sentiment analysis on movie reviews using the IMDb dataset. The KAN model integrates traditional neural network capabilities with knowledge from a graph to enhance the sentiment classification task.

NST-for-Artistic-Image-Creation

This project focuses on Neural Style Transfer (NST), a technique that applies the style of one image to the content of another image, creating a new, stylized image. NST leverages deep learning models, particularly Convolutional Neural Networks (CNNs), to extract and combine the content and style features of images.

TattooAI

Text-Generation-using-T5

This project demonstrates the use of Transformers for text generation using the T5 model. The project includes the necessary code for training the model on a custom dataset and generating new text.

Text-Summarization-using-BART

This project demonstrates text summarization using the BART (Bidirectional and Auto-Regressive Transformers) model. BART is a transformer model trained as a denoising autoencoder and is effective for text generation tasks such as summarization.

Train-your-LLM

This repository contains code and resources for training, fine-tuning, and deploying large language models using Hugging Face's Transformers library.

SreeEswaran/Train-your-LLM

This repository contains code and resources for training, fine-tuning, and deploying large language models using Hugging Face's Transformers library.

SreeEswaran/Build-RAG-Agent-with-LLM

This repository contains the implementation of a Retrieval-Augmented Generation (RAG) agent using Large Language Models (LLMs). RAG agents combine the power of information retrieval with text generation, enabling applications such as intelligent question-answering systems, and more.

SreeEswaran/Image-classification-using-CNN

This project demonstrates image classification using a Convolutional Neural Network (CNN) on the CIFAR-10 dataset. The model is trained to classify images into one of 10 classes.

SreeEswaran/NST-for-Artistic-Image-Creation

This project focuses on Neural Style Transfer (NST), a technique that applies the style of one image to the content of another image, creating a new, stylized image. NST leverages deep learning models, particularly Convolutional Neural Networks (CNNs), to extract and combine the content and style features of images.

SreeEswaran/TattooAI

SreeEswaran/Text-Summarization-using-BART

This project demonstrates text summarization using the BART (Bidirectional and Auto-Regressive Transformers) model. BART is a transformer model trained as a denoising autoencoder and is effective for text generation tasks such as summarization.

SreeEswaran/chatApp

A simple chat application using html, css, expressjs, nodejs and sqlite3

SreeEswaran/ChattingApplication

SreeEswaran/compilerDesign

SreeEswaran/GripnGo

SreeEswaran/Handwritten-digit-Classification

This project implements a Convolutional Neural Network (CNN) to classify handwritten digits from the MNIST dataset. The model is built using TensorFlow and Keras.

SreeEswaran/Image-Captioning-Transformer

This project demonstrates an image captioning model using a Transformer architecture. The model takes an image as input and generates a descriptive caption. We use the COCO dataset for training and evaluation.

SreeEswaran/Image-Classification-using-EfficientNet

This project uses a pre-trained EfficientNet model to classify images into different categories. The model is fine-tuned on a custom dataset for this purpose.

SreeEswaran/Image-Generation-using-GANs

SreeEswaran/KAN-based-Movie-Review-Sentiment-Analysis

This project showcases the implementation of a Knowledge-Aware Neural Network (KAN) for sentiment analysis on movie reviews using the IMDb dataset. The KAN model integrates traditional neural network capabilities with knowledge from a graph to enhance the sentiment classification task.

SreeEswaran/Multi-Modal-Sentiment-Analysis-with-Transformers

This project leverages the power of transformer models to perform sentiment analysis on both text and images. It uses BERT for text sentiment analysis and a pre-trained vision transformer (ViT) for image sentiment analysis.

SreeEswaran/Object-Detection-YOLOv5

This project demonstrates object detection using YOLOv5. The model is trained on a custom dataset and can detect objects in new images. YOLOv5 is a state-of-the-art object detection model known for its speed and accuracy, making it suitable for real-time applications.

SreeEswaran/Resume-Semantic-Search

SreeEswaran/RL-Game-Playing

SreeEswaran/Sentiment-Analysis-using-BERT

SreeEswaran/SportsScheduler-CSP

SreeEswaran/SreeEswaran

Know a lil about my tech background

SreeEswaran/Text-Generation-using-T5

This project demonstrates the use of Transformers for text generation using the T5 model. The project includes the necessary code for training the model on a custom dataset and generating new text.

SreeEswaran/Basics-of-RAGs

SreeEswaran/ResumeSemanticSearch

SreeEswaran/SreeEswaran.github.io

SreeEswaran/Workshop