Summary

This is a foundational chapter in our journey through advanced NLP problems. Many advanced models use building blocks such as BiRNNs. First, we used the TensorFlow Datasets package to load data. Our work of building a vocabulary, tokenizer, and encoder for vectorization was simplified through the use of this library. After understanding LSTMs and BiLSTMs, we built models to do sentiment analysis. Our work showed promise but was far away from the state-of-the-art results, which will be addressed in future chapters. However, we are now armed with the fundamental building blocks that will enable us to tackle more challenging problems.

Armed with this knowledge of LSTMs, we are ready to build our first NER model using BiLSTMs in the next chapter. Once this model is built, we will try to improve it using CRFs and Viterbi decoding.