Creating a Neural Language Model using LSTMs and calculating perplexity score of the model.
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Updated
Apr 15, 2022 - Python
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).
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.
Natural Language Processing Lab Experiments
Pytorch based Neural Network Language Modeling (NNLM) Toolkit for easier and faster NNLM research and development. Result of my Master's Thesis work.
N-gram and neural word-level language models
Language Modeling using Recurrent Neural Networks implemented over Tensorflow 2.0 (Keras) (GRU, LSTM)
This repository Contains all the assignments for a course Natural Language Processing in IIT Patna
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
Deep learning models in Python
Generating High-Quality Query Suggestion Candidates for Task-Based Search - ECIR'18
Materials for the MSc Thesis "Interpreting Neural Language Models for Linguistic Complexity Assessment" and related works.
Improving Language Model Performance through Smart Vocabularies
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
Generating text sequences using attention-based Bi-LSTM
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