Telugu OCR using RNN

TV Script Generation with RNN with Udacity

Character Encoding RNN

RNN-LSTM model that classifies movie reviews

Harnessing NLP for Historical Text Analysis: A Case Study on the Indus Valley Civilization

Classifying whether a disaster tweet is real or not using LSTM and GloVe word embeddings

A lightweight, deep learning library written in pure Python

In this kaggle competition I used TimeDistributed layer of keras to classify if questions asked on quora are same or duplicate.

RNN language model implemented in chainer.

Projects from deeplearning.ai's course hosted on Coursera

Code and scripts for training, testing and sampling auto-regressive recurrent language models on PyTorch with RNN, GRU and LSTM layers

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).

Classifies the movie reviews as positive or negative using LSTM Networks

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. (Supports all Models both Luong and Bhanadau).

attempt at implementing "Memory Architectures in Recurrent Neural Network Language Models" as a part of the ICLR 2018 reproducibility challenge

The main task of the character-level language model is to predict the next character given all previous characters in a sequence of data, i.e. generates text character by character.