An Image Captioning implementation of a CNN Encoder and an RNN Decoder in PyTorch.

Interact with a trained chatbot that uses sequence to sequence model with luong attention mechanism over jointly trained encoder-decoder modules and implementation of greedy search decoding module.

With Captionify, users can upload an image or enter an image URL to generate a descriptive caption that accurately describes the contents of the image.

DIGITAL LOGIC DESIGN

Long short-term memory based semi-supervised encoder-decoder for early prediction of failures in self-lubricating bearings

Encoder Decoder Model for Image Captioning

Summarizing and shortening the text using deep learning.

The project consists in building a Transformer Encoder to predict deaths from cardiovascular diseases. An important part is to exploit missing values in order not to lose data information. Data augmentation is performed by adding missing values and noise to training records.

Explore the world of large language models , featuring comprehensive source codes and guides on deploying them effectively in production environments

Text generation is the task of generating text with the goal of appearing indistinguishable to human-written text.

This project seeks to create a comprehensive system for summarising research papers by harnessing the latest advancements in AI and NLP. By merging abstractive text summarization with LLMs and the RAG methodology, we anticipate developing a unique and effective approach to extracting valuable insights from research papers

Explore diverse computer vision projects using Transfer Learning(TL), Convolutional Neural Networks (CNN), Autoencoder and more in this collaborative repository

Using sequence-to-sequence neural network for computing.

Training FMNIST and MNIST dataset on Feed Forward Neural Network

Transformers Intuition

A deep learning model to generate captions for images as inputs

CVAE implementation on MNIST dataset using PyTorch

A basic server-client system for courses registration. In this assignment we have implemented a server based on the reactor design pattern and the encoder-decoder model. Our server is built in java and the client side is built in cpp.

Certification Artificial Intelligence Engineer Final Project