Hola! Welcome back to the follow-up article on LSTMs. In this article we shall discuss 2 more architectures which are very similar to LSTMs. They are Bi-LSTMs and GRUs (Gated Recurrent Units). As we saw in our previous article, the LSTM was able to solve most problems of vanilla RNNs and solve a few important NLP problems easily with good data. The Bi-LSTM and GRU can be treated as architectures which have evolved from LSTMs. The core idea will be the same with a few improvements here and there.
Hello again, glad to welcome you back to this article on Text Classification in the NLP Tutorials series. In our previous posts we had a detailed overview on the fundamental text representation — CountVectorizer & Tf-Idf Vectorizer and also the two most prominent Word Embeddings — Word2Vec & GloVe. In this article we will put our knowledge to task — Build a Text Classification model using all these techniques and analyse the results.