The following are my takeaways from the talk, Embedding work in NLP.

The following are some of the takeaways from this medium article.

In this brief post, I would like to pen down my thoughts on two aspects: Heuristics and Non-Intepretability of models. Let’s look at word embedding matrix. If you take a bunch of words and want to build a learning algorithm, the first task is to convert the text in to a bunch of numbers. The two popular algorithms that have revolutionized the field of NLP are Skipgram method and CBOW method.

This post illustrates CNN LSTM Models that can be fit to simple time series data.

This post illustrates the early stopping callback in Keras.