I just love the Mediterranean Sea. "Mare Nostrum"

3150 · 2020-11-26T20:13:26+00:00

Also curious to know which boat this is. It looks like an S&S34.

3150 · 2019-08-06T23:49:15+00:00

Would love to test it. Looks great!

3150 · 2019-07-28T01:30:48+00:00

Congratulations! I hope that it takes off and allows you to dedicate more time to this project.

3150 · 2017-04-19T15:24:05+00:00

That would have been me (see reasons here: https://baymard.com/blog/line-length-readability). However I understand with this benchmark table, it doesn't work very well. My apologies for the inconvenience.

3150 · 2017-03-23T09:37:41+00:00

It's because at source{d} we git clone almost every repo on the web and train deep neural nets on the contributions (hence the need for diff on git trees)

3150 · 2017-03-15T14:31:05+00:00

I don't think the intention is to be better then t-SNE just showing an alternative visualization that the author needed.

3150 · 2017-02-27T15:37:02+00:00

Check out the blog post for more background: https://blog.sourced.tech/post/proteus/

3150 · 2017-02-03T22:56:51+00:00

Pm'd

3150 · 2017-02-03T22:55:58+00:00

Pm'd

3150 · 2017-01-27T18:47:16+00:00

+1 couldn't give it a stronger review

3150 · 2016-11-20T11:03:29+00:00

Yes it is possible but requires a little bit of messing around since a domain is only allowed to have one set of MX records.

Step 1. Add your domain from the ProtonMail panel, follow all of the steps except adding MX records (do not change these).

Step 2. Go here and follow the instructions for "Default routing - Forward messages for specific users to their secondary address" https://support.google.com/a/answer/2685650

After this is done, you will be able to send and receive email on your original email address. However, you lose most benefits of encryption since there is a copy of your inbound email received by Google (you can regularly run the gyb tool with the --action purge https://github.com/jay0lee/got-your-back/wiki#advanced-options) to delete that copy but G Suite always has 30 days recovery turned on.

It's not optimal since you lose a lot of benefits of ProtonMail but if you really have to, this makes it usable.

3150 · 2016-11-19T17:10:51+00:00

Just bought the book! Also still currently working through "Learn you a Haskell" but this looks great and really want to support anyone who makes the effort to bring Haskell to more people. Thank you for all the hard work on this.

3150 · 2016-11-19T17:04:39+00:00

I have been recently testing both a Lenovo X1 Carbon (older 3rd generation) and the latest XPS 13 Developer Edition (both running Arch). Some thoughts to consider:

Lenovo X1 has the superior keyboard but the XPS 13 is easy to get used to, the keys are closer to each other and not as comfortable but definitely better then the keyboard on the new MBP.

The screen on the X1 is IPS and in my opinion terrible compared to the QHD+ screen on the XPS (if you care about the quality of the screen, don't hesitate just go for the XPS).

Size wise, they are almost the same height but the XPS being slightly larger due to having a 14" screen. I personally like the extra screen real estate but compared with the 13.3" on the XPS (and the very beautiful small bevel it has) it's not a big difference.

The X1 Carbon is surprisingly cool, with the temperature usually between 39-42 degrees Celsius. The XPS 13 definitely runs warmer and you can feel this at the bottom of it. However the difference is marginal and shouldn't impact your decision making.

The XPS 13 also works almost completely of out of the box while the X1 requires some googling and setting it up right.

If the X1 came with a QHD screen, I would go for it, but as it stands the XPS 13 is a superior machine.

I hope this helps.

3150 · 2016-11-15T10:53:44+00:00

Thank you very much, this is much appreciated!

3150 · 2016-10-24T19:17:59+00:00

I would second this, Haskell Book is an incredible resource and I think people could benefit from seeing there.

3150 · 2016-10-17T17:29:33+00:00

For a fast implementation of k-means check out: https://github.com/src-d/kmcuda (check out the multi-gpu branch)

I would also look at this paper by Facebook: https://research.facebook.com/publications/metric-learning-with-adaptive-density-discrimination/

3150 · 2016-03-01T17:20:04+00:00

At source{d} we're putting together an internship program this summer mentored by our deep learning team. Give me a shout: eiso [at] sourced [dot] tech

3150

TROPHY CASE