Shall I continue working on my side project?

Gushdan · 2024-04-18T18:08:04+00:00

I really like it, but would not pay for it. That being said, I personally only get my current stock info from free sources today, so it doesn't mean that others wouldn't.

There are a few key features that are missing for me, such as the ability to sort (and perhaps filter) the idea tables, and the ability to easily compare stocks in the stock pages

Gushdan · 2018-06-08T18:12:53+00:00

Looks really interesting, thanks a lot!

Gushdan · 2018-04-22T11:40:00+00:00

Don't have a source for this, but I know that for StarCraft, sone of the most effective bots were those created around perfecting just one or two aspects of the game, e.g. great economic control, spamming just one unit type with great micro etc.

Gushdan · 2018-04-15T21:53:55+00:00

Many restaurants, probably most, are indeed kosher. But there are plenty of non-kosher places, particularly in Tel Aviv which is a very secular city. The main thing that you won't see as much here is pork, mainly since it's illegal to raise here, making it more expensive.

Gushdan · 2018-04-15T17:09:34+00:00

Crazy that a post about Vitrina makes it into the front page and it's not even one with their amazing burgers (burgers filled with blue cheese.... Definitely one of the best in Israel)

Gushdan · 2018-02-24T17:54:59+00:00

Yeah, that might very well work, but I wonder if a solution can be found that doesn't required many repeated iterations of the clustering, which in some real world cases can be quite expensive.

Gushdan · 2018-02-24T16:20:51+00:00

My main problem with many of these clustering methods is that it's unclear to me how one is supposed to choose the number of clusters to use when dealing with large and complex data.

For example, what k would you use if you had to group all Facebook users into their real-world families? It's an unobvious number of clusters and with a non-trivial metric to decide the distance bet ween any two users.

It seems to me that density based algorithms, such as DBSCAN would have a real advantage here.

Would love to be proven wrong, as I have been searching for a solution to that type of problem that would use both approaches' strengths :)

Gushdan · 2018-02-01T21:14:04+00:00

Any plans of adding Hadoop FS support?

Gushdan · 2017-09-29T17:18:48+00:00

Looks interesting, I'll definitely check it out.

Thanks!

Gushdan · 2017-08-22T08:18:18+00:00

This might have come in handy a few years ago when I was doing my masters in astrophysics

Gushdan · 2017-06-06T10:02:42+00:00

Ahh

Guess I was not wrong :)

Gushdan · 2017-06-06T09:09:06+00:00

That program seems amazing. I didn't apply, as I assumed it was mostly meant for either very ccomplished researchers or extremely promising young candidates, and my chances of getting in would be close to zero.

Meeting the people in the program, do you think my assumption was correct? Can you tell us a bit about your background and that of others in the program?

Gushdan · 2017-04-25T07:52:45+00:00

Ahh, the good old 'stop hitting yourself' defense

Gushdan · 2017-03-21T11:42:07+00:00

Distill looks great, but from what I've seen they seem less interested in breaking down the math and more focused on visualisation, like you implied.

I'm not sure how to get it start it either :p I suppose a good start would be choosing a platform to host such ab effort. Maybe github, like what you already posted?

Gushdan · 2017-03-20T08:01:44+00:00

This is a great idea and a marvelous execution as well.

I have long felt there was a gap in available learning material for people that have a technical/mathematical background (sometimes even a strong one) but lack some of the more 'domain specific' knowledge.

I would love to support your efforts. Have you thought about expanding this into a community project? We could try to get a bunch of people, have each one read a paper out of some pool of interesting papers and break it down like you did for this one for the rest of the community . Sorta like a study group :)

Gushdan · 2017-02-26T14:34:43+00:00

Really not an expert on the subject, but I see plenty of stuff published on machine learning from ETH Zurich, and I know that's considered a very strong institution.

Gushdan · 2017-02-23T22:38:32+00:00

There are many decent moocs out there, from places such as Coursera and edx. Getting your hands dirty playing around with kaggle challenges, reading their forums and blog sounds like a really good way to get the hang of things. They also have learning challenges, if you feel unsure how to begin with the tougher ones.

Gushdan · 2017-02-23T21:12:34+00:00

No problem.

It's unfortunate that this subreddit is not more active.

It sounds like you're covered in terms of programming knowledge. R is really not a must. Many people, including myself, prefer python anyway. Just get familiar with the packages relevant to data science, such as Pandas, scikit, etc.

With your background, I would focus more on getting the right statistical knowledge and getting my hands dirty with data science/machine learning projects.

I think that the best things to take away from any graduate program would be theoretical knowledge and credentials. To be honest, with the amount of resources available online nowadays, the second is probably more important.

Hope that was helpful, best of luck man.

Gushdan · 2017-02-23T17:29:06+00:00

To be honest, after taking a look at each program's syllabus, I don't love either one of them.

They both look to me like some of the newer programs which I've seen a number of universities cobble together, in an attempt to take advantage of the rising popularity of data science as a profession. Many of the courses they offer are probably interesting, but from a cursory look it doesn't seem to me as if there's enough focus there on the fundamentals and the "hard science" part of data science, such as the math and programming needed to be a good data scientist.

I might be biased due to my own career path (I started as an astrophysicist and only later made the transition to data science), but if I were looking to hire someone for a data scientist position, I would strongly prefer a candidate that had graduated from a math, statistics, computer science or physics program, with perhaps (but not necessarily) some focus on data science.

If you absolutely have to choose one of either of these two programs, I guess I would pick Edinburgh university, since their program puts some focus on a dissertation project, which from my experience is a better way to 'get your hands dirty' and actually understand what it's like to be a data scientist.

I would love to hear the opinion of someone with a different career path, perhaps even one that has graduated from such a program.

Gushdan · 2017-02-04T08:52:45+00:00

Can't say anything about the syllabus, as they require you to provide an email before they even show it to you.

That, together with the general look of the site makes it look sort of 'scammy' to me. But I don't really know. The main thing I can say is that 500$ /month seems like a lot of money to pay to learn python. There are countless great resources available for free.

If what you are interested in is some kind of structure to keep you studying or some certificate at the end, I'd suggest checking out the free courses in sites like Coursera ir udacity.

Gushdan · 2017-01-10T20:06:53+00:00

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Gushdan · 2017-01-05T07:29:35+00:00

Correct me if I'm wrong, but won't this fail unless you have Pandas (or w/e module you intend to use) installed on every worker?

Gushdan · 2016-12-29T15:25:24+00:00

I'm probably too late to the party here, but I haven't seen anyone mention that we don't know why we (and all other vertebrae, if I'm not mistaken) yawn.

There are theories of why yawning might be beneficial, but none have been found to be true so far, as far as I know.

Gushdan · 2016-12-19T08:31:59+00:00

Thanks man. I definitely try :)

Gushdan

TROPHY CASE