#962 overall
spaCy Course
spaCy
1 recommender · 1 thread · recommended in 1 year, 2019 · score 0.7
An interactive online course from spaCy, the NLP library, covering how to use spaCy for natural language processing tasks. It is built around the library's pipelines, tokenization, and related NLP workflows.
One commenter calls it an "extremely slick interactive course" and describes spaCy as a highly recommended Swiss Army knife library for NLP, recommended by its package author Ines Montani.
Recommendations by year
20062026
For deep learning / neural networks, I think these are the best balance of theory and practice (not to mention great visualizations): http://cs231n.github.io
More on the intuition/theory side for NNs, but Michael Nielsen’s book is highly recommended: http://neuralnetworksanddeeplearning.com
For NLP, you can try this extremely slick interactive course on spaCy (highly recommended Swiss Army knife library for NLP) from package author Ines Montani: https://course.spacy.io
The Keras tutorials are solid, here’s one on seq2seq models: https://blog.keras.io/a-ten-minute-introduction-to-sequence-...
For more cutting edge NLP, it looks like the fast.ai course covers the Transformer model (the basis of BERT, GPT-2, et al. This is a great overview of that architecture: http://nlp.seas.harvard.edu/2018/04/03/attention.html
And PyTorch implementations of Transformer models can be found here: https://github.com/huggingface/pytorch-pretrained-BERT/blob/...
LMK if anyone wants more, I have a learning resource hoarding problem.