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Google's Free Deep Learning Course

udacity.com

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Re: Google's Free Deep Learning Course

#11

Post by stared »

When it comes to the course itself (I've just started it) it looks nice, but the (initial) questions tend to be vague.

E.g. in the first question with code I had to reverse-engineer what they mean (including passing values in a format, which I consider non-standard (transpose!)). The first open-ended questions were entirely "ahh, you meant this aspect of the question".

Otherwise, the course (the general level, pace, overview) seems nice.

EDIT:

The IPython Notebook tasks (i.e. the core exercises) are nice.

Re: Google's Free Deep Learning Course

#12

Post by it_learnses »

Would it be beneficial for me as a developer to take these machine learning courses? I took a course in the uni a while back and know the general techniques, but I'm not sure how it would help me in my career unless I'm doing some cutting edge work in the field or focusing on a machine learning career, in which case wouldn't I need to be pursuing a postdoc or something in it?

Re: Google's Free Deep Learning Course

#13

Post by drcode »

it_learnses wrote: post #12

Would it be beneficial for me as a developer to take these machine learning courses? I took a course in the uni a while back and know the general techniques, but I'm not sure how it would help me in my career unless I'm doing some cutting edge work in the field or focusing on a machine learning career, in which case wouldn't I need to be pursuing a postdoc or something in it?

It sort of makes you wonder if we're looking at a future where something like 5 teams composed of 1000 of the top researchers each are going to build the premier ML systems, and those teams can then solve most generalized ML tasks.

Most other programmers wouldn't be able to contribute much value in a world that worked like this.

This perhaps mirrors how the chip market works, which similarly involves a limited number of researchers involved in advanced manufacturing techniques that are highly specialized and mostly a mystery to other people in the technology field.

Re: Google's Free Deep Learning Course

#14

Post by stared »

it_learnses wrote: post #12

Would it be beneficial for me as a developer to take these machine learning courses? I took a course in the uni a while back and know the general techniques, but I'm not sure how it would help me in my career unless I'm doing some cutting edge work in the field or focusing on a machine learning career, in which case wouldn't I need to be pursuing a postdoc or something in it?

Likely. Data analysis (of which ML is an important part) is needed in many places, from entry-level to top-level.

I am a data science freelancer and I mostly do projects for IT-dominated companies. First, I was surprised that such companies need some external help with relatively simple tasks; only later I discovered that top-notch performance in webdev (or even: algorithms) does not mean that someone is able to do simplest data analysis.

For data science / ML - I know a lot of openings in which they are looking for "data scientists", but what they mean is software engineers with at least a slight idea what is data analysis.

When it comes to deep learning in particular - I don't know.

Re: Google's Free Deep Learning Course

#15

Post by zo1 »

stared wrote: post #14
it_learnses wrote: post #12

Would it be beneficial for me as a developer to take these machine learning courses? I took a course in the uni a while back and know the general techniques, but I'm not sure how it would help me in my career unless I'm doing some cutting edge work in the field or focusing on a machine learning career, in which case wouldn't I need to be pursuing a postdoc or something in it?

Likely. Data analysis (of which ML is an important part) is needed in many places, from entry-level to top-level. I am a data science freelancer and I mostly do projects for IT-dominated companies. First, I was surprised that such companies need some external help with relatively simple tasks; only later I discovered that top-notch performance in webdev (or even: algorithms) does not mean that someone is able to do s…

>"For data science / ML - I know a lot of openings in which they are looking for "data scientists", but what they mean is software engineers with at least a slight idea what is data analysis."

I've been wanting to get into this field recently. Do you have more info about these openings, perhaps?

Re: Google's Free Deep Learning Course

#16

Post by conventionalmem »

drcode wrote: post #13
it_learnses wrote: post #12

Would it be beneficial for me as a developer to take these machine learning courses? I took a course in the uni a while back and know the general techniques, but I'm not sure how it would help me in my career unless I'm doing some cutting edge work in the field or focusing on a machine learning career, in which case wouldn't I need to be pursuing a postdoc or something in it?

It sort of makes you wonder if we're looking at a future where something like 5 teams composed of 1000 of the top researchers each are going to build the premier ML systems, and those teams can then solve most generalized ML tasks. Most other programmers wouldn't be able to contribute much value in a world that worked like this. This perhaps mirrors how the chip market works, which similarly involves a limited number…

But there may be a larger market to hire people who know how to use the tools they design.

Re: Google's Free Deep Learning Course

#17

Post by magicmu »

How accessible is a course like this with no prior knowledge of linear algebra? I know it's listed in the pre-reqs, but with a good head for math and lots of calc, is it something that could be picked up along the way? I'm normally pretty bold about stuff like that, but I know it's a core part of deep learning / ML. If it's really necessary, if anyone has any resources for linear algebra run-throughs it would be greatly appreciated!!

Re: Google's Free Deep Learning Course

#18

Post by stared »

zo1 wrote: post #15
stared wrote: post #14

Earlier quoted context omitted.

Likely. Data analysis (of which ML is an important part) is needed in many places, from entry-level to top-level. I am a data science freelancer and I mostly do projects for IT-dominated companies. First, I was surprised that such companies need some external help with relatively simple tasks; only later I discovered that top-notch performance in webdev (or even: algorithms) does not mean that someone is able to do s…

>" For data science / ML - I know a lot of openings in which they are looking for "data scientists", but what they mean is software engineers with at least a slight idea what is data analysis. " I've been wanting to get into this field recently. Do you have more info about these openings, perhaps?

Now I don't track offers (I get contracts through recommendations/networking), so I may be not up-to date. My background is different (PhD in quantum physics), so for me stats/data/ML is simple, but software architecture, algorithms - not as much.

When 3 years ago I was looking for data science internships, most of interview were strictly in software engineering. (I got into a more data-analysis oriented.) Even when I applied to Google a year ago (and failed), all non-trivial questions where in software engineering (some with data-oriented paradigms, tough).

Look at https://medium.com/@rchang/my-two-year-journey-as-a-data-sci... - the taxonomy of "Type A Data Scientist" vs "Type B Data Scientist" is useful. You want to apply for the "B" or even - software engineer in a company which deals with data and is open to shifting roles.

Going back to the interviews: I see that the set of questions is entirely different. E.g. if the first question is "how to invert a binary table" or "how to test if a black-box number generator is fair". But sometimes it is not clear from the job opening.

EDIT:

If you are interested in my background: http://p.migdal.pl/2015/12/14/sci-to-data-sci.html

Re: Google's Free Deep Learning Course

#19

Post by mrborgen »

magicmu wrote: post #17

How accessible is a course like this with no prior knowledge of linear algebra? I know it's listed in the pre-reqs, but with a good head for math and lots of calc, is it something that could be picked up along the way? I'm normally pretty bold about stuff like that, but I know it's a core part of deep learning / ML. If it's really necessary, if anyone has any resources for linear algebra run-throughs it would be grea…

Haven taken this course (though I will), but check out Andrew Ng's Coursera's ML course. He gives a crash course in linear algebra. It helped me a lot in my endeavours in ML & neural nets. I also like to learn as I go along, and this intro was just about enough to get started.

Re: Google's Free Deep Learning Course

#20

Post by jskonhovd »

magicmu wrote: post #17

How accessible is a course like this with no prior knowledge of linear algebra? I know it's listed in the pre-reqs, but with a good head for math and lots of calc, is it something that could be picked up along the way? I'm normally pretty bold about stuff like that, but I know it's a core part of deep learning / ML. If it's really necessary, if anyone has any resources for linear algebra run-throughs it would be grea…

I would start with the nano degree program if you don't have any prior knowledge of ML.

Udacity has a Linear Algebra review course, but I don't believe it is public for now. I had taken a linear algebra course before I took the GT ML class, but I wasn't a expert by any means. I don't believe you will need a deep understanding of linear algebra before taking this class. Singular value decomposition might come up. I think if you are familiar with everything in the following pdf you should be fine.

http://minireference.com/static/tutorials/linear_algebra_in_...

If you are motivated, you will do fine. Good luck!

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