Ask HN: How to get started with machine learning?

Post by tsm » Sat, Oct 15, 2016, 4:16 PM UTC

sanderjd wrote: post #58

jotto wrote: post #2

If you want to jump right in with "hello world" type TensorFlow (a tool for machine learning), see https://news.ycombinator.com/item?id=12465935 (how to fit a straight line using TensorFlow) If you like to study/read: the famous Coursera Andrew Ng machine learning course: https://www.coursera.org/learn/machine-learning If you just want course materials from UC Berkeley, here's their 101 course: https://news.ycombinat…

What is a good "hello world" project for machine learning? That is, what problem can I solve or question can I answer with minimal ceremony, and ideally with multiple techniques / technologies so that I can compare them? Is it this house price estimation like in your last link, or is there something better than that?

Post by sanderjd » Sat, Oct 15, 2016, 4:40 PM UTC

sgk284 wrote: post #62

sanderjd wrote: post #58

Earlier quoted context omitted.

What is a good "hello world" project for machine learning? That is, what problem can I solve or question can I answer with minimal ceremony, and ideally with multiple techniques / technologies so that I can compare them? Is it this house price estimation like in your last link, or is there something better than that?

Kaggle has a number of starter challenges. See https://www.kaggle.com/c/titanic for one related to predicting the survival of passengers on the Titanic.

Post by daturkel » Sat, Oct 15, 2016, 4:58 PM UTC

krosaen wrote: post #60

I took the summer off to learn enough ML to transition from a career in software engineering & product / leadership type roles to ML. I suggest for a first round learning practical tools and techniques so you can start applying supervised learning techniques right away while also starting to build a more solid foundation in probability & statistics for future deeper understanding of the field. I've written about my c…

Post by caretStick » Sat, Oct 15, 2016, 5:27 PM UTC

tanderson92 wrote: post #59

caretStick wrote: post #53

Newton's method and other numerical methods are the hello world of machine learning. Why numerical methods? * They might produce the right answer * They frequently do * They are easy to visualize or imagine * You get used to working with a routine that is both fallible but quite simple and remarkably able to work in a wide variety of situations. This is what machine learning does, but there are more sophisticated rou…

> Newton's method and other numerical methods are the hello world of machine learning. Newton's method and other similar numerical methods are the hello world of a branch of mathematics known as 'numerical analysis' and scientific computing. This is not Machine Learning.

Post by dschiptsov » Sat, Oct 15, 2016, 5:41 PM UTC

sgk284 wrote: post #62

sanderjd wrote: post #58

Earlier quoted context omitted.

What is a good "hello world" project for machine learning? That is, what problem can I solve or question can I answer with minimal ceremony, and ideally with multiple techniques / technologies so that I can compare them? Is it this house price estimation like in your last link, or is there something better than that?

Kaggle has a number of starter challenges. See https://www.kaggle.com/c/titanic for one related to predicting the survival of passengers on the Titanic.