Solution for the Quora Insincere Questions Classification Kaggle competition.
-
Updated
Apr 10, 2023 - Python
Solution for the Quora Insincere Questions Classification Kaggle competition.
A simple and easy to understand NLP teaching
Generate captions from images
Natural Language Processing
Neural Machine Translation by Jointly Learning to Align and Translate paper implementation
Caption Images with Machine Learning
Bangla Conversational Chatbot using Bidirectional LSTM with Attention Mechanism
Implementation of GRU-based Encoder-Decoder Architecture with Bahdanau Attention Mechanism for Machine Translation from German to English.
Seq2Seq model implemented with pytorch, using Bahdanau Attention and Luong Attention.
Neural Machine Translation (NMT) with pivot and triangulation approaches
A multi-layer bidirectional seq-2-seq chatbot with bahdanau attention.
ExpressNet is a ready-to-use, weightless text classification model architecture that you can import and start training immediately.
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.
This repository contains TensorFlow/Keras models for implementing an Encoder-Decoder architecture for sequence-to-sequence tasks. It includes components such as Encoder, Decoder, Embedding Layer, LSTM Layer, Attention Mechanism, and more.
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.
Tensorflow 2.0 tutorials for RNN based architectures for textual problems
Sequence 2 Sequence with Attention Mechanisms in Tensorflow v2
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).
Master Project on Image Captioning using Supervised Deep Learning Methods
Add a description, image, and links to the bahdanau-attention topic page so that developers can more easily learn about it.
To associate your repository with the bahdanau-attention topic, visit your repo's landing page and select "manage topics."