- Gain deepened understanding on NLP
- Hands-on experience implementing seq2seq models with attention with TensorFlow
- Familiarize model training using TPUs
- Theoretical understanding on Encoder-Decoder based seq2seq conversational agent with attentions
- Explore and preprocess a variety of conversational datasets
- Build encoder-decoder model with attention:
1. Shared embedding layer for encoder and decoder
2. Two GRU layer for both encoder and decoder
3. Bidirectional encoder
3. Decoder with Luong's attention
- Define training loop with teacher-forcing
- Inference with both greedy and beam search
- Deploy the model with Flask
- Clone the repo
- Create an virtual environment and install the packeges using: pip install -r requirements.txt
- run flask app: python app.py