I’m taking a quick dive into current machine learning, with an emphasis on natural language processing for Tinderbox.
I did some research in machine learning during the second golden age of AI, back in the 1980s. But I’ve not really worked with the tools since Terry Winogrand’s SHRDLU was young. Deep learning changed everything, and all my learning about deep learning has been book learning. I’m not sure that’ll do. So, I’m currently up to my ears in word2vec, Jupyter Notebook, and Tensor Flow backends.
This is probably too technical and too limited for much blogging, but I do need a link dump; perhaps this might be handy to someone down the road.
- CS224n: Natural Language Processing with Deep Learning (Stanford)
- A Course in Machine Learning (Hal Daumé III) — a lovely textbook
- Core ML Survival Guide (Matthijs Hollemans) — nooks and crannies of Apple’s implementation
- Inner workings of word2vec (Chris McCormick)
- Deep learning with PyTorch (Soumith Chintala)
- Cornell movie dialog corpus
- Tutorial: python and numpy. Refreshingly concise introduction.
- Tutorial: sci.py