sentence-classification

I’d suggest: https://fast.ai - good intro on practical neural networks. I wrote a guide to ML based NLP. We identify if a sentence is a question, statement or command using neural networks: https://github.com/lettergram/sentence-classification The truth is you don’t need to understand all the math right away with neural networks. Mostly it’s getting an understanding of why you use a given layer, bias, etc and when. Once you get some intuition then I’d learn the math. That’s at least how I instruct others. In any case, there are lots of guides for any flavor. I’d start with deep learning and focus on the “practical” then move to the “theoretical”.

For those interested, I’ve done similar work in the past. I’ve also written a guide along with explanations of how it works (on sentence classification): https://github.com/lettergram/sentence-classification It uses Keras and goes through everything from encodings, to the way various networks function, to hyperparameter tuning.

For those interested, I recently wrote a guide on using neural networks for NLP[1]. I wrote the guide with the explicate goal of trying to help the people understand NLP (sentence classification) without the need to understand the math. I cover word embeddings: https://austingwalters.com/word-embedding-and-data-splitting... As well as FastText: https://austingwalters.com/fasttext-for-sentence-classificat... Hope someone finds it useful. [1] https://github.com/lettergram/sentence-classification