rnn-encoder-decoder

Adaptive Associative Compute is a proposed neural architecture on the core principle, not all information should receive the same amount of memory and compute.

Game Of Thrones Generative ChatBot Trained using Seq2Seq Model on Game Of Thrones Subs and Book data

USC graduate level Language Models in NLP course

Sequence to Sequence Models in PyTorch

RNN Encoder-Decoder in PyTorch

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.

End-to-end Automatic Speech Recognition for Madarian and English in Tensorflow

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.

using a combination of CNN and RNN for generating captions for images

Simple TensorFlow implementation of skip-thought vectors

Code For Medium Article "How To Create Data Products That Are Magical Using Sequence-to-Sequence Models"

Inspired by the neural style algorithm in the computer vision field, we propose a high-level language model with the aim of adapting the linguistic style.

A simple chatbot built using ML in Python. The data in the intents json file can be modified. This model works for all kinds of input data json file, most accurately in English language.

1st place solution

Official source code of "Fast Adaptive RNN Encoder-Decoder for Anomaly Detection in SMD Assembly Machine"

Assignment 2: Neural Machine Translation in 'Statistical Machine Translation' course by Dr. Roee Aharoni at Bar-Ilan University.

Automatically describing the content of an image fundamental problem in artificial intelligence that connects computer vision and natural language processing.

Papers covering a few of my Deep Learning Projects.