Deep learning models in Python

Bengio's Neural Probabilistic Language Model implemented in Matlab which includes t-SNE representations for word embeddings.

Pytorch implementation of a simple GRU word-level language model trained on Donald Trump's tweets.

Improving Language Model Performance through Smart Vocabularies

Generating text sequences using attention-based Bi-LSTM

Generating High-Quality Query Suggestion Candidates for Task-Based Search - ECIR'18

Language Modeling using Recurrent Neural Networks implemented over Tensorflow 2.0 (Keras) (GRU, LSTM)

N-gram and neural word-level language models

Projects for Data Mining and Analytics

Materials for the MSc Thesis "Interpreting Neural Language Models for Linguistic Complexity Assessment" and related works.

Creating a Neural Language Model using LSTMs and calculating perplexity score of the model.

Towards Comprehensive Understanding of Bias in Pre-trained Neural Language Models: A Survey with Special Emphasis on Affective Bias

Implementation of a simple neural language model (multi-layer perceptron) from scratch for next word prediction

Basic concepts which are used in NLP such as : Language model, Neural Language model, Word embedding, Text classification, Bert, RNN, LSTM, GRU, Attention, Transformers.

Implementation of "A Neural Probabilistic Language Model" by Yoshua Bengio et al. - Tensorflow

Natural Language Processing Lab Experiments

Classification of case.law cases by landmark cases from www.law.cornell.edu

Advanced file format fuzzer based-on deep neural language models.

This repository Contains all the assignments for a course Natural Language Processing in IIT Patna

Pytorch based Neural Network Language Modeling (NNLM) Toolkit for easier and faster NNLM research and development. Result of my Master's Thesis work.