RNNs and Transformers Course Repository

This repository contains the code and resources for the RNNs and Transformers course offered by Udacity. The course covers the following topics:

• Simple RNN
• LSTM
• Transformers

The code in this repository is implemented using the PyTorch library.

Overview

The course covers the fundamentals of recurrent neural networks (RNNs) and transformers, two powerful deep learning architectures used for natural language processing (NLP), time-series analysis, and other sequential data tasks.

Skills Learned

By completing this course, you will gain the following skills:

• Understanding of the theory and architecture of RNNs and transformers
• Building and training RNN and transformer models using PyTorch
• Preprocessing and tokenizing text data for NLP tasks
• Working with pre-trained transformer models and the HuggingFace library

Tools Used

The following tools and libraries are used in this course:

• Python 3
• PyTorch
• HuggingFace Transformers
• NumPy
• pandas