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

Chapter 9: Attention and Memory Augmented Networks

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

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

Master Project on Image Captioning using Supervised Deep Learning Methods

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.

A simple and easy to understand NLP teaching

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

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.

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).

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

Solution for the Quora Insincere Questions Classification Kaggle competition.

Natural Language Processing

Neural Machine Translation (NMT) with pivot and triangulation approaches