Book Content
chapters • 12h40m total length
1. Essentials of NLP
2. Understanding Sentiment in Natural Language with BiLSTMs
3. Named Entity Recognition (NER) with BiLSTMs, CRFs and Viterbi Decoding
4. Transfer Learning with BERT
5. Generating Text with RNNs and GPT-2
6. Text Summarization with Seq2seq Attention and Transformer Networks
7. Multi-Modal Networks and Image Captioning with ResNets and Transformer Networks
8. Weakly Supervised Learning for Classification with Snorkel
9. Building Conversational AI Applications with Deep Learning
10. Installation and Setup Instructions for Code
