QuillGPT is an implementation of the GPT decoder block based on the architecture from Attention is All You Need paper by Vaswani et. al. in PyTorch. Additionally, this repository contains two pre-trained models — Shakespearean GPT and Harpoon GPT, a Streamlit Playground, Containerized FastAPI Microservice, training - inference scripts & notebooks.

This collection of notebooks is based on the Dive into Deep Learning Book. All of the notes are written in Pytorch and the d2l/torch library

This repo contains my implementaions of notebooks in TensorFlow (not in Trax which is used in the course) of Natural Language Processing Specialization: Course4 (NLP with Attention) by deeplearning.ai on Coursera

This colab`s notebook contains pipeline for creating one-to-one machine translation model based on Seq2SeqTransformer

Implementation notebooks and scripts of Artistic CNN Models and Generative Models like GANs, VAEs, GMMs, Boltzmann Machine etc. in TensorFlow, and Python. This repo aims to understand and make amazing things out of Neural Network layers.

Jupyter Notebook tutorial on Attention Mechanisms, Position Embeddings and Random Fourier Feature based approximations. Created for Imperial College Deep Learning Course

The notebook explains the various steps to obtain the results of publication: "Is Space-Time Attention All You Need for Video Understanding?"

A set of notebooks that explores the power of Recurrent Neural Networks (RNNs), with a focus on LSTM, BiLSTM, seq2seq, and Attention.

Curated implementation notebooks and scripts of deep learning based natural language processing tasks and challenges in TensorFlow.

This repository contains Jupyter Notebook Files of some state of the art projects that I completed during my internship program in deeplearning.ai. The project files are divided into 5 main categories or respective courses that the deeplearning.ai provides.