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I don't know much about AI but for ML specifically Elements of Statistical Learning is fantastic. I find its explanations a lot easier to understand than other

by 256 9y ago

I don't know much about AI but for ML specifically Elements of Statistical Learning is fantastic. I find its explanations a lot easier to understand than other resources. I recommend you skim through it to get a taste. Additionally if you prefer lectures ETHZ has recordings of their ML class[1]. The best way to learn the details is of course to read the original papers. This is especially true for following along with the latest developments in deep learning. [1] https://www.ethz.ch/content/vp/en/lectures/d-infk/2017/autumn/252-0535-00L.html https://www.ethz.ch/content/vp/en/lectures/d-infk/2017/autum...

jphamtastic 9y ago
For someone who might want a higher-level primer, Introduction to Statistical Learning is also great. http://www-bcf.usc.edu/~gareth/ISL/ http://www-bcf.usc.edu/~gareth/ISL/
v3gas 9y ago
I'm working my way through Elements now. Do you by any chance know of any lectures specifically based on it? And solutions to the exercises there? I have found it hard to find (good) solutions.
- 256 9y ago
  I haven't looked for any lectures because I learn best from reading books. So, I don't know, sorry. I'm interested in a solution set too.
- koulvi 9y ago
  The Machine Learning Course offered by Prof. Ravindran at Indian Institute of Technology (IIT- Madras) uses ESLR. The course is free to enroll and you will have weekly assignments. https://onlinecourses.nptel.ac.in/noc18_cs26/preview https://onlinecourses.nptel.ac.in/noc18_cs26/preview
  - v3gas 9y ago
    Thanks!!
infimum 9y ago
> Additionally if you prefer lectures ETHZ has recordings of their ML class[1]. I took that class back in 2015. I found that the lectures were sometimes hard to follow, unless you already know the concepts (which creates a bit of a catch-22). For me the most valuable moments were, when Prof. Buhmann got sidetracked by some anecdotes. Would absolutely recommend, but maybe not as a starting point.
QasimK 9y ago
Does anyone know how Elements of Statistical Learning compares to Introduction to Statistical Learning which is also from the same authors?
- imh 9y ago
  ISLR is a simplified version of ESL.

by 256 9y ago

jphamtastic 9y ago

For someone who might want a higher-level primer, Introduction to Statistical Learning is also great. http://www-bcf.usc.edu/~gareth/ISL/ http://www-bcf.usc.edu/~gareth/ISL/

v3gas 9y ago

I'm working my way through Elements now. Do you by any chance know of any lectures specifically based on it? And solutions to the exercises there? I have found it hard to find (good) solutions.

256 9y ago
I haven't looked for any lectures because I learn best from reading books. So, I don't know, sorry. I'm interested in a solution set too.
koulvi 9y ago
The Machine Learning Course offered by Prof. Ravindran at Indian Institute of Technology (IIT- Madras) uses ESLR. The course is free to enroll and you will have weekly assignments. https://onlinecourses.nptel.ac.in/noc18_cs26/preview https://onlinecourses.nptel.ac.in/noc18_cs26/preview
- v3gas 9y ago
  Thanks!!

infimum 9y ago

> Additionally if you prefer lectures ETHZ has recordings of their ML class[1]. I took that class back in 2015. I found that the lectures were sometimes hard to follow, unless you already know the concepts (which creates a bit of a catch-22). For me the most valuable moments were, when Prof. Buhmann got sidetracked by some anecdotes. Would absolutely recommend, but maybe not as a starting point.

QasimK 9y ago

Does anyone know how Elements of Statistical Learning compares to Introduction to Statistical Learning which is also from the same authors?

imh 9y ago
ISLR is a simplified version of ESL.