HN Academy

The best online courses of Hacker News.

Hacker News Comments on
Statistical Learning

edX · Stanford University · 3 HN comments

HN Academy has aggregated all Hacker News stories and comments that mention edX's "Statistical Learning" from Stanford University.
Course Description

Learn some of the main tools used in statistical modeling and data science. We cover both traditional as well as exciting new methods, and how to use them in R. Course material updated in 2021 for second edition of the course textbook.

HN Academy Rankings
  • Ranked #12 this year (2022) · view
Provider Info
This course is offered by Stanford University on the edX platform.
HN Academy may receive a referral commission when you make purchases on sites after clicking through links on this page. Most courses are available for free with the option to purchase a completion certificate.

Hacker News Stories and Comments

All the comments and stories posted to Hacker News that reference this url.
I liked the EdX Statistical Learning course by Trevor Hastie and Robert Tibshirani, it's a great introduction to statistical modeling and data science (assuming you already have a solid math and statistics background): https://www.edx.org/course/statistical-learning

It is not too math heavy, and the focus is on basic, interpretable approaches and concepts like:

- linear and polynomial regression

- logistic regression and linear discriminant analysis

- cross-validation and the bootstrap

- model selection and regularization methods (ridge and lasso)

- tree-based methods, random forests and boosting

- support-vector machines

- neural networks and deep learning

- survival models; multiple testing

- some unsupervised learning methods like principal components and clustering (k-means and hierarchical).

The instructors are really articulate and passionate about teaching well. As a bonus, there are guest speakers about every second week including Jerome Friedman and Geoff Hinton.

I suggest first understanding machine learning in general before jumping into deep learning. The book ISLR2 is very accessible and starts with linear regression and works through many other methods including neural networks. There is a Edx course based on the book.

https://www.statlearning.com/

https://www.edx.org/course/statistical-learning

It looks pretty good. The introduction, ANN and Bayesian chapters look just as relevant today as they would have been when this book was published, 25 years ago. I like that hypotheses testing is covered.

Chapter 9, Genetic Algorithms and Programming, was hot stuff back then, and research continues today, I went to an interesting seminar a few months ago given by a genetic programming researcher, but from the perspective of solving a ML problem, less useful to the beginner. If you have a regression of classification problem, few people will be trying genetic algorithms to solve it.

Chapter 10 - 12 is rule based systems, for example Prolog, which again was thought of being the future back then, and as much as I love using Prolog, it is not part of modern ML curriculum.

Chapter 13 is short chapter on RL, which is popular today (DeepMind).

All that said, if a beginner wants to pick one book, I would suggest ISLR2, also free and has a Edx course

https://www.statlearning.com/

https://www.edx.org/course/statistical-learning

harry8
Is that the same one that was on the stanford edx clone site?

edx seems to be putting more behind a paywall and jacking up the price in a way that's pretty disappointing. That one is what $150 for the computer to tell you if the numbers you typed in some boxes is what was expected, for example. I mean, looking up the answer in the back of the book is worth that? The certificate is worth absolutely nothing to anyone save for how it makes them feel.

082349872349872
RL ca. 1961: https://en.wikipedia.org/wiki/Matchbox_Educable_Noughts_and_...

(which I learned about from a Fred Saberhagen short)

HN Academy is an independent project and is not operated by Y Combinator, Coursera, edX, or any of the universities and other institutions providing courses.
~ [email protected]
;laksdfhjdhksalkfj more things
yahnd.com ~ Privacy Policy ~
Lorem ipsum dolor sit amet, consectetur adipisicing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.