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

Generating text sequences using attention-based Bi-LSTM

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

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

Improving Language Model Performance through Smart Vocabularies

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

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

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

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

Deep learning models in Python

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

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

Natural Language Processing Lab Experiments

Projects for Data Mining and Analytics

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.

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

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

Master Thesis Project - different phases of analyses developed for the LangLearn shared task (EVALITA 2023).