Study Group in Italy

Hello, is there other people from Italy joining the course?

If so, it could be of interest to connect :slight_smile:


Hi Daniele,

I’m from Ireland but what would you say to create EU group as time is not so different between EU countries :slight_smile:



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Very good idea @Michal_w!

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Hi Daniele and Michal,

I come from Italy too: let’s stay in touch!

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Francesco is here. Let’s stay in touch!

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Andrea. Glad to meet y’all! :wink:

So if I’m not making mistakes, we’ll have the first lesson at 3 o’clock, October 23. Am I right? :thinking:

Like I said previously, good idea! We could use the EU study group for everything but local meetups.

Hi everybody,
this is Riccardo from Italy too.

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Hello everyone!!!

This is Federico, I am Italian but I am now living in Finland!!!

Hi all! Here I’am… Andrea from Milan, Italy. let’s roll :slight_smile:

Hello guys, did you attend the live class this “morning”?

This year I can’t make it (job hours are not that compatible with waking up in the middle of the night), but if you can I strongly suggest following live.
It’s a completely different experience!

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I did, just get up :wink:
@DavideBoschetto : totally agree!

What about trying to solve a classification problem as study group to practice with new library?
Could be a Kaggle dataset or competition:

About 70mb:

About 116MB:

Other “small” (and usually fast to train and to make experiments) dataset for image classification to pick:

… On small datasets like that you can even practice with CPU!

I attended too!
Now at work… :thinking:

I would try to focus on specific real-problems/issues that, if solved, could be of direct and immediate benefit of those in need.

For instance:!Synapse:syn4224222/wiki/401743

More over, if we can apply our learnings as a group to specific problems, we can also double-check what the state of the art currently states.

What do you think guys?

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Other available resources on the same topic:

Full data-set:

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I’m in! Choose the one you like.

BTW: I’ve used v1 to this old competition yesterday and got very good results at the first try: 32 errors over 4462 in the validation set.

Hi guys, I’m in too.

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Ciao @ste,
thanks for the reply!

I found the histological data-set for breast cancer interesting for several reasons:

  1. It seems that images normalization used in the paper uses a different criteria than the standard one proposed by @jeremy in the class

  2. It seems balanced

  3. There are state-of-the-art metrics

  4. Can provide an impact to health of women

It would be great to run this group-session “live” (via hangout?)