Deep RNN model(Encoder - Decoder) with Attention mechanism and Beam Search decoding for langauge translation.
An Intelligent Approach for Translation / Transliteration using Neural Networks
Text Processing RNN leverages RNN and LSTM models for advanced text processing. It features deep learning techniques for NLP tasks, utilizing GloVe for word embeddings, aimed at both educational and practical applications.
Papers covering a few of my Deep Learning Projects.
RNN-LSTM model that classifies movie reviews
En utilisant, un RNN (réseau de neurones récurrents), je vais générer de la musique du style du groupe ‘The Chainsmokers’ c’est-à-dire de la musique POP.
iPython notebooks for teaching and mishmash
End-to-end text-to-speech synthesis based on deep learning
A deep neural network that functions as part of an end-to-end machine translation pipeline. The completed pipeline will accept English text as input and return the French translation.
Projects from deeplearning.ai's course hosted on Coursera
Udacity NLP foundation nanodegree learning
A collection of Tensorflow tutorials focusing on RNN and VAE. Work in progress!
Sequence Models Assignments from Coursera Deep Learning Specialzation
Minimal Seq2Seq model with Attention for Neural Machine Translation in PyTorch
2019 1st semester Machine Learning Final Project at SNU
In this project, I generated Seinfeld TV scripts using RNNs.This project is part of udacity deep learning nanodegree program. The Neural Network will generate a new, "fake" TV script, based on patterns it recognizes in this training data.
PyTorch implementation of "Effective Approaches to Attention-based Neural Machine Translation" using scheduled sampling to improve the parameter estimation process.
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