Didn't read the document, but hopefully it mentions PageRank, the prime example of using probabilistic graphical models to rank nodes in a directed graph. More info: https://www.amazon.com/Probabilistic-Graphical-Models-Princi...
I've heard that Google and Baidu essentially started at the same time, with the same algorithm discovery (PageRank). Maybe someone can comment on if there was idea sharing or if both teams derived it independently.
> 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.
I've heard that Google and Baidu essentially started at the same time, with the same algorithm discovery (PageRank). Maybe someone can comment on if there was idea sharing or if both teams derived it independently.
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-Approa...
[2] https://www.amazon.com/Pattern-Recognition-Learning-Informat...
[3] https://www.amazon.com/Probabilistic-Graphical-Models-Princi...
[4] https://youtu.be/-z5lKPHcumo
[0] https://www.amazon.com/Probabilistic-Graphical-Models-Princi...