11–20 of 87 posts
Having the examples only in R was a pain when teaching with it while using Python. I hope they‘ll now turn this into a series of Jupyter notebooks and distribute it through Colab or similar.
Off topic, but it's very interesting to observe the ratio of upvotes / comments. On any given chatGPT topic, there are hundreds of comments usually. Here, so far 100 upvotes, only 7 comments. The book looks great - and given the authors, it almost certainly is (I will buy it for sure). It makes me think though about the state of 'ML / AI / Data Science' - and the cynic part of me thinks that this upvotes / comments r…
Off topic, but it's very interesting to observe the ratio of upvotes / comments. On any given chatGPT topic, there are hundreds of comments usually. Here, so far 100 upvotes, only 7 comments. The book looks great - and given the authors, it almost certainly is (I will buy it for sure). It makes me think though about the state of 'ML / AI / Data Science' - and the cynic part of me thinks that this upvotes / comments r…
This kind of books are key to getting started with Machine Learning/AI, and this particular book is a very good one. I started my ML journey with this book.
There is a lot of hype around AI and it is going to be like the dotcom bubble.
Unlike Crypto, AI has real uses right now and I am saying this not taking into account any LLM products. But there is also a lot of hype and wishful thinking, and this bubble is going to burst and hurt a lot of people. But that won't stop people making real money in the short term. Many hypers I know understand this well.
But AI is here to stay. And even after the bubble bursts, there will be real uses of AI all around us.
Sidney Siegel, N. John Castellan, Jr. 'Nonparametric Statistics for the Behavioral Sciences, Second Edition', ISBN 0-07-057357-3, McGraw-Hill, New York, 1988.
So, "nonparametric" means make no assumptions about a probability distribution based on parameters. Or, call the material distribution-free.
E.g., get to see about resampling plans -- tiny assumptions, really simple, darned cleaver, quite generally useful, especially appropriate for computing. Might use resampling to get more information from the data from "A - B" tests.
Off topic, but it's very interesting to observe the ratio of upvotes / comments. On any given chatGPT topic, there are hundreds of comments usually. Here, so far 100 upvotes, only 7 comments. The book looks great - and given the authors, it almost certainly is (I will buy it for sure). It makes me think though about the state of 'ML / AI / Data Science' - and the cynic part of me thinks that this upvotes / comments r…
Might consider, say, Sidney Siegel, N. John Castellan, Jr. 'Nonparametric Statistics for the Behavioral Sciences, Second Edition', ISBN 0-07-057357-3, McGraw-Hill, New York, 1988. So, "nonparametric" means make no assumptions about a probability distribution based on parameters . Or, call the material distribution-free . E.g., get to see about resampling plans -- tiny assumptions, really simple, darned cleaver, quite…
Off topic, but it's very interesting to observe the ratio of upvotes / comments. On any given chatGPT topic, there are hundreds of comments usually. Here, so far 100 upvotes, only 7 comments. The book looks great - and given the authors, it almost certainly is (I will buy it for sure). It makes me think though about the state of 'ML / AI / Data Science' - and the cynic part of me thinks that this upvotes / comments r…
https://github.com/melling/ISLR
There’s an edX course from the authors: