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I've been doing the Coursera ML course the past few weeks(started on the 22th of August). I can only give it my highest recommendation, it really is a great cou

by K0nserv 10y ago

I've been doing the Coursera ML course the past few weeks(started on the 22th of August). I can only give it my highest recommendation, it really is a great course. I did computer science in university(2.5 years) and have a decent grasp of calculus and linear algebra. I've also been programming for 9 or so years. I've found the course to be surprisingly simple and intuitive, but this probably varies with how comfortable you are with the math in the course.

albertojacini 10y ago
I completely agree. It was also very well balanced between theory and practice.
wrcwill 10y ago
Is it the UofW course or Andrew ng's?
- K0nserv 10y ago
  Andrew ng's
mamon 10y ago
I'm also doing this course right now. Having MSc degree in computer science helps a lot, although I got my diploma as long as 10 years ago, but still some math sticked with me. My biggest regret is that my day job as developer does not leave me with much time for more Octave programming. Of course I do excercises, but that's not enough to be good ML developer. However, I think that just having a lot of sample code would be helpfull if I ever make ML my full time job. Especially considering that the excercises themselves are pretty interesting (handwriting recognition, image compression, etc).
noname123 10y ago
>Coursera ML course the past few weeks(started on the 22th of August). I can only give it my highest recommendation. I'm taking the edX series of courses on Machine Learning with Apache Spark. It is a pretty good class and covers linear algebra and the basic ETL workflow, plus selection of models, model parameters tweaking parameters etc., study cases involving user ad clicks prediction and PCA analysis of neural synapse data of jellyfishes. However, my biggest fear is that re-learning different matrix manipulations, walk-through of logistics regression, PCA and SVM will be similar to learning Spanish in high school without immersion, learning guitar scales without improvising with it, learning mappings of different Madden key-combo's; I remember learning all of these mathematical syntactical operations in high school, and have an eerie feeling of once grasping these concepts concretely once and yet only knowing it vaguely. It is nice to re-learn these things, like refreshing myself with a rolodex of Spanish verb conjugation, only to go back to the CRUD work I deal with on a daily basis and fade back to oblivion. Not sure about the Coursera class, the structure of the edX courses are presented in Python Juypter notebooks where you fill in the code snippets. It is fun and addictive to solve each exercise as a mini-puzzle; but not sure how much it'll stick vs. if one had to take an concrete problem and take its pieces and puzzles from start to finish, without the hands-holding. I think perhaps Cousera courses have "capstone" projects - curious if anyone have had experience doing one? In lieu of one on the edX course, I think I plan to grok some papers with some large genomic dataset and/or financial time-series and try to replicate their result.
- drothlis 10y ago
  Yes, the Coursera ML course is equally hand-holdey. (I'd still recommend it anyway.)
- deleted 10y ago
  [deleted]
- K0nserv 10y ago
  Yeah this is definitely a fear of mine, it does feel like you can get through the course and mostly understand the concept without getting the tools to fully apply the learnings. Like drothlis points out the Coursera course it very hand-holdey too. For the exercises you are given a set of Matlab/Octave files and your objective is to fill in a few of them with the correct implementation of specific steps. It doesn't feel like you ever get to perform the full task, I plan to redo some of the exercises with Python after I finishes the course.
- larve 10y ago
  I end up trying to reimplement the whole notebook from scratch, deleting all the code cells from the original notebook.
- stickperson 10y ago
  Is this the series you're referring to: https://www.edx.org/xseries/data-science-engineering-apache-spark https://www.edx.org/xseries/data-science-engineering-apache-...
chris_st 10y ago
I'm taking this course as well, and I'm really pleased with how practical it is, and how much "here's how to figure out how to do better" advice and techniques there are. Really, it's a great model for teaching technical subjects in general.
hello_newman 10y ago
I totally agree. I took that course as well, and thought his explanations were amazing, but because I'm just a rails/angular developer and do not have the required math background, I definitely got lost and could not keep up the pace. I'm currently taking math now so I will be able to participate in something like this in the future.
trahn 10y ago
Did they get you with the email that the first assignment was due as well?! They sure got me. :D I had been meaning to do the course for quite a while and had started it once before, but now with the deadlines I am finally following along. :)

by K0nserv 10y ago

albertojacini 10y ago

I completely agree. It was also very well balanced between theory and practice.

wrcwill 10y ago

Is it the UofW course or Andrew ng's?

K0nserv 10y ago
Andrew ng's

mamon 10y ago

I'm also doing this course right now. Having MSc degree in computer science helps a lot, although I got my diploma as long as 10 years ago, but still some math sticked with me. My biggest regret is that my day job as developer does not leave me with much time for more Octave programming. Of course I do excercises, but that's not enough to be good ML developer. However, I think that just having a lot of sample code would be helpfull if I ever make ML my full time job. Especially considering that the excercises themselves are pretty interesting (handwriting recognition, image compression, etc).

noname123 10y ago

>Coursera ML course the past few weeks(started on the 22th of August). I can only give it my highest recommendation. I'm taking the edX series of courses on Machine Learning with Apache Spark. It is a pretty good class and covers linear algebra and the basic ETL workflow, plus selection of models, model parameters tweaking parameters etc., study cases involving user ad clicks prediction and PCA analysis of neural synapse data of jellyfishes. However, my biggest fear is that re-learning different matrix manipulations, walk-through of logistics regression, PCA and SVM will be similar to learning Spanish in high school without immersion, learning guitar scales without improvising with it, learning mappings of different Madden key-combo's; I remember learning all of these mathematical syntactical operations in high school, and have an eerie feeling of once grasping these concepts concretely once and yet only knowing it vaguely. It is nice to re-learn these things, like refreshing myself with a rolodex of Spanish verb conjugation, only to go back to the CRUD work I deal with on a daily basis and fade back to oblivion. Not sure about the Coursera class, the structure of the edX courses are presented in Python Juypter notebooks where you fill in the code snippets. It is fun and addictive to solve each exercise as a mini-puzzle; but not sure how much it'll stick vs. if one had to take an concrete problem and take its pieces and puzzles from start to finish, without the hands-holding. I think perhaps Cousera courses have "capstone" projects - curious if anyone have had experience doing one? In lieu of one on the edX course, I think I plan to grok some papers with some large genomic dataset and/or financial time-series and try to replicate their result.

drothlis 10y ago
Yes, the Coursera ML course is equally hand-holdey. (I'd still recommend it anyway.)
deleted 10y ago
[deleted]
K0nserv 10y ago
Yeah this is definitely a fear of mine, it does feel like you can get through the course and mostly understand the concept without getting the tools to fully apply the learnings. Like drothlis points out the Coursera course it very hand-holdey too. For the exercises you are given a set of Matlab/Octave files and your objective is to fill in a few of them with the correct implementation of specific steps. It doesn't feel like you ever get to perform the full task, I plan to redo some of the exercises with Python after I finishes the course.
larve 10y ago
I end up trying to reimplement the whole notebook from scratch, deleting all the code cells from the original notebook.
stickperson 10y ago
Is this the series you're referring to: https://www.edx.org/xseries/data-science-engineering-apache-spark https://www.edx.org/xseries/data-science-engineering-apache-...

chris_st 10y ago

I'm taking this course as well, and I'm really pleased with how practical it is, and how much "here's how to figure out how to do better" advice and techniques there are. Really, it's a great model for teaching technical subjects in general.

hello_newman 10y ago

I totally agree. I took that course as well, and thought his explanations were amazing, but because I'm just a rails/angular developer and do not have the required math background, I definitely got lost and could not keep up the pace. I'm currently taking math now so I will be able to participate in something like this in the future.

trahn 10y ago

Did they get you with the email that the first assignment was due as well?! They sure got me. :D I had been meaning to do the course for quite a while and had started it once before, but now with the deadlines I am finally following along. :)