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> study textbooks. Do exercises. Treat it like academic studying This. Highly recommend Russel & Norvig [1] for high-level intuition and motivation. Then Bisho
by boltzmannbrain 8y ago
> study textbooks. Do exercises. Treat it like academic studying
This. Highly recommend Russel & Norvig [1] for high-level intuition and motivation. Then Bishop's "Pattern Recognition and Machine Learning" [2] and Koller's PGM book [3] for the fundamentals.
Avoid MOOCs, but there are useful lecture videos, e.g. Hugo Larochelle on belief propagation [4].
FWIW this is coming from a mechanical engineer by training, but self-taught programmer and AI researcher. I've been working in industry as an AI research engineer for ~6 years.
[1] https://www.amazon.com/Artificial-Intelligence-Modern-Approach-3rd/dp/0136042597 https://www.amazon.com/Artificial-Intelligence-Modern-Approa...
[2] https://www.amazon.com/Pattern-Recognition-Learning-Information-Statistics/dp/0387310738 https://www.amazon.com/Pattern-Recognition-Learning-Informat...
[3] https://www.amazon.com/Probabilistic-Graphical-Models-Principles-Computation/dp/0262013193 https://www.amazon.com/Probabilistic-Graphical-Models-Princi...
[4] https://youtu.be/-z5lKPHcumo https://youtu.be/-z5lKPHcumo
- jimmy-dean 8y agoOof those are all dense reads for a new comer... For a first dip into the waters I usually suggest Introduction to Statistical Learning. Then from there move into PRML or ESL. Were you first introduced to core ML through Bishop? +1 for a solid reading list.
- sampo 8y agoPGMs were in fashion in 2012, but by 2014 when Deep Learning had become all the rage, I think PGMs almost disappeared from the picture. Do people even remember PGMs exist now in 2019?
- KidComputer 8y agoYou'll find plate models, PGM junk, etc in modern papers on explicit density generative models and factorizing latents on such models.
- vazamb 8y agoPGMs also provide the intuition behind GANs and variational autoencoders.
- srean 8y agoFashion is relevant only if you want to approach it as a fashion industry.
- magoghm 8y agoI would also include some books about statistics. Two excellent introductory books are: Statistical Rethinking https://www.amazon.com/Statistical-Rethinking-Bayesian-Examples-Chapman/dp/1482253445/ref=sr_1_1?ie=UTF8&qid=1546306434&sr=8-1&keywords=statistical+rethinking https://www.amazon.com/Statistical-Rethinking-Bayesian-Examp... An Introduction to Statistical Learning http://www-bcf.usc.edu/~gareth/ISL/ http://www-bcf.usc.edu/~gareth/ISL/
- godelmachine 8y agoHands up for Bishop and Russel Norvig. Russel Norvig should be treated as a subtle intro to AI. The start Bishop to understand concepts.