Multiclass Text Classification Using Deep Learning

Before we go any further into text classification, we need a way to represent words numerically in a vocabulary. Because most of our ML models require numbers, not text. One way to achieve this goal is by using the one-hot encoding of word vectors, but this is not the right choice. Given the structure of one-hot encoded vectors, the similarity is always going to be 0 between different words. Word2Vec overcomes the above difficulties by providing us with a fixed-length (usually much smaller than the vocabulary size) vector representation of words.