This repository contain various types of attention mechanism like Bahdanau , Soft attention , Additive Attention , Hierarchical Attention etc in Pytorch, Tensorflow, Keras

Configurable Encoder-Decoder Sequence-to-Sequence model. Built with TensorFlow.

Chapter 9: Attention and Memory Augmented Networks

Tensorflow 2.0 tutorials for RNN based architectures for textual problems

A multi-layer bidirectional seq-2-seq chatbot with bahdanau attention.

Generate captions from images

Image Captioning is the process of generating textual description of an image. It uses both Natural Language Processing and Computer Vision to generate the captions.

Master Project on Image Captioning using Supervised Deep Learning Methods

A simple and easy to understand NLP teaching

Seq2Seq model implemented with pytorch, using Bahdanau Attention and Luong Attention.

Neural Machine Translation by Jointly Learning to Align and Translate paper implementation

Implementation of GRU-based Encoder-Decoder Architecture with Bahdanau Attention Mechanism for Machine Translation from German to English.

Bangla Conversational Chatbot using Bidirectional LSTM with Attention Mechanism

s-atmech is an independent Open Source, Deep Learning python library which implements attention mechanism as a RNN(Recurrent Neural Network) Layer as Encoder-Decoder system. (only supports Bahdanau Attention right now).

A language translator based on a very simple NLP Transformer model, backed by encoder, decoder and a Bahdanau Attention Layer in between, implemented on TensorFlow.

ExpressNet is a ready-to-use, weightless text classification model architecture that you can import and start training immediately.

Sequence 2 Sequence with Attention Mechanisms in Tensorflow v2

Implemented an Encoder-Decoder model in TensorFlow, where ResNet-50 extracts features from the VizWiz-Captions image dataset and a GRU with Bahdanau attention generates captions.

Solution for the Quora Insincere Questions Classification Kaggle competition.

Natural Language Processing