- Neural Machine Translation
- Discover some of the shortcomings of a traditional seq2seq model and how to solve for them by adding an attention mechanism, then build a Neural Machine Translation model with Attention that translates English sentences into German.
- Text Summarization
- Compare RNNs and other sequential models to the more modern Transformer architecture, then create a tool that generates text summaries.
- Question Answering
- Explore transfer learning with state-of-the-art models like T5 and BERT, then build a model that can answer questions.
- Chatbot
- Examine some unique challenges Transformer models face and their solutions, then build a chatbot using a Reformer model.
