How relevant is “A super harsh guide to machine learning” for someone who is just tinkering with machine learning?

• deeplearning-notes

  71 353 0.0

  Notes for Deep Learning Specialization Courses led by Andrew Ng.

My recommendations are worth little, I'm just starting through all this stuff myself. I'm currently taking the Deep Learning specialization on Coursera and trying to map out what else I should be doing.

• go

  7 24,288 4.0

  The Open Source Data Science Masters (by datasciencemasters)

  

One of the comments points to datasciencemasters.org, which has gotten a bit stale, but has a link to Coursera's Data Science specialization which is on my short list for what to do next (and that arguably should probably be done before deep learning, but whatever.) There may be other good nuggets on that page. -The Deep Learning Book emits some strong must-read vibes, like one of those slightly cursed items that almost glow in the dark.

• WorkOS

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• arxiv-sanity-lite

  17 1,082 0.0 Python

  arxiv-sanity lite: tag arxiv papers of interest get recommendations of similar papers in a nice UI using SVMs over tfidf feature vectors based on paper abstracts.

Arxiv-sanity seems like it'll be useful eventually, once I've at least learned the common vocabulary and syntax of ML paper writers.

Suggest a related project