Machine Learning with scikit-learn

http://amueller.github.io/sklearn_tutorial/#/

by derpapst • 13 years ago

72 12 13 years ago

amueller.github.io

I cannot tell you how much I hate these drip-feed presentations. There isn't even an indication of how long it goes for. The early stuff is obvious (for me) - how many times do I have to click to get to the interesting bits?

There might be some great stuff here, but many of your potential audience will never find out, because they'll give up.

jkldotio• 13 years ago

Most reveal.js based presentations you can press "esc" and get a slide overview, although that's of limited use. Slides in general are simply not as useful as a reasonable web page if they don't have the presentation along with them in audio or video. It's a peculiar part of HN culture to link to just slides, I don't know of any other group that does it.

A far better introduction to sci-kit learn is the project's examples page, http://scikit-learn.org/stable/auto_examples/index.html, which you can use to get example code and data to generate each type of graph. The documentation on the rest of the site is also of very high quality.

aidos• 13 years ago

I was going to say that it's not really that much of a problem - until I got to page 7 and couldn't scroll down to see the code because I'm on a laptop. Instead I have to Select All - Copy - Paste into editor. That's unforgivable.

Edit: on closer inspection it's just the last couple of lines that I'm missing - but it's still very annoying.

sjtgraham• 13 years ago

I know what I'm doing tonight. Great idea including sample data to play with in the library! Is that the MNIST data set?

dhammack• 13 years ago

Here's how to get MNIST, from the sklearn docs:

>> from sklearn.datasets import fetch_mldata
>> mnist = fetch_mldata('MNIST original', data_home=custom_data_home)

I think the handwritten digits dataset used in the presentation is just a subset of MNIST; MNIST is 28x28 and the handwritten digits are 8x8.

gallamine• 13 years ago

Here's a link to the other available sample datasets: http://scikit-learn.org/stable/datasets/index.html

blauwbilgorgel• 13 years ago

Andreas Mueller is one of the core devs of scikit learn.

He is active on Kaggle.com too.

For more practical ML projects see: https://github.com/amueller

toisanji• 13 years ago

He has only done one competition as noted in his slides.

tucson2• 13 years ago

I'd like to know more about slide 6:

http://amueller.github.io/sklearn_tutorial/#/6

Why the [Classification][100K sample?] checkpoint?

And more info in general about this whole cheat-sheet.

IanCal• 13 years ago

SGD is fast but not necessarily more accurate. If you've got lots and lots of data, then a simple yet fast approach is likely to be a good choice to start with.

tucson2• 13 years ago

Thanks.

I also found a blog post that figured the diagram, with some background infos:

http://peekaboo-vision.blogspot.de/2013/01/machine-learning-...

Machine Learning with scikit-learn

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