6 ms·

Ask HN: Best online courses for machine learning?

65 points by aliirz 8y ago

Ask HN: What are some of the best online resources to jump into practical machine learning

notoriousjpg 8y ago
This'd be a safe bet https://www.coursera.org/learn/machine-learning https://www.coursera.org/learn/machine-learning
sidkhanooja 8y ago
Contrary to popular opinion, I find that Andrew Ng's Intro to ML (on Coursera/Stanford) focuses too much on basic math and theory - which doesn't detract from the course's quality, but makes the course a drudgery to go through. Programming exercises involve a single line or two, and that too in Octave - which was all the rage back when the course was launched, but it's not so useful now. Instead, start with this - https://www.fast.ai https://www.fast.ai It emphasizes practicality to the extreme - you are only taught theory/domain knowledge when needed. The instructor's amazing, the massive scale of knowledge imparted boggles the mind, and you feel like you've accomplished something when you're finished with it. Best of all, it's free. And you can start Deep Learning there too when you're done with ML, if you feel the need (or interest).
- k4ch0w 8y ago
  I'd second this class. I have done both and if you're brand new to machine learning I'd do fast.ai first. You gain a greater understanding from Andrew's course, but if you're not going to become a practitioner fast.ai is better.
- jackallis 8y ago
  i have to agree with you here. It's good class if you want to focus on theory and veer towards academic part of ML.
- philonoist 8y ago
  There should also be some sort of polls for these sort of questions or at least for mapping goals. I past polls if any in ...yc.com/news feed. How do I go about it?
- ihvck 8y ago
  I really love the code first approach of Fast.ai, I'm impressed by teaching style of Jeremy its clear, succinct, and to the point.
priyanka2019 8y ago
Get over the stress of searching for a course that will be fruitful for your career. Join a Digital Marketing Course to enjoy a successful career all throughout your life. This course is in the best courses after 12th. Because this is the most progressive field which has unlimited growth opportunities and Digital Marketing alone will have 20 lakh job opportunities by 2020. Learn this course to be an expert before you complete your graduation. You can become a part of the fastest growing Industry and see your benefits grow with every passing year. Since this field is broad, you can select your profession according to your interest. There are many posts available in Digital Marketing Field- 1. SEO Executive 2.Social Media Marketer 3.Content Writer 4.Community Manager 5.PPC Executive 6.Email Marketing Executive 7.Web Designer 8.Graphic Designer 9.Digital Sales Expert 10.-commerce Marketing Manager This is one of the least unfolded pitch in India. So, this field has a huge scope to grow in. I will suggest higher studies in Digital Marketing Course. Because that can take you very high, you can work for leading companies and you can get a really handsome amount of salary. Read more at https://iiadm.in/courses-after-12th https://iiadm.in/courses-after-12th
UsernameTaken5 8y ago
There's a free intro course here: https://www.udemy.com/machine-learning-intro-for-python-developers/ https://www.udemy.com/machine-learning-intro-for-python-deve...
jackallis 8y ago
This depends upon you first telling us at what level you are? beg, int, ad.
- cromiium 8y ago
  Not OP but I'm a beginner. Any recommendations different than what was already said?
solomatov 8y ago
This one: https://see.stanford.edu/course/cs229 https://see.stanford.edu/course/cs229 It's a recording of CS229 at Stanford. This course is much harder and more thorough than the one on coursera.
nwsm 8y ago
Udemy's Machine Learning A-Z course: https://www.udemy.com/machinelearning/ https://www.udemy.com/machinelearning/ All lessons in R and Python. Wide range of content.
Isamu 8y ago
Google ML crash course: https://developers.google.com/machine-learning/crash-course/ https://developers.google.com/machine-learning/crash-course/ Facebook field guide to machine learning: https://research.fb.com/the-facebook-field-guide-to-machine-learning-video-series/ https://research.fb.com/the-facebook-field-guide-to-machine-... Training on Machine Learning with AWS: https://aws.amazon.com/training/learning-paths/machine-learning/ https://aws.amazon.com/training/learning-paths/machine-learn...
- simple_phrases 8y ago
  Can anyone comment on whether these are worth the time investment versus more traditional courses?
  - ultrasounder 8y ago
    I haven't taken any of these courses. There were these courses from Amazon https://aws.amazon.com/training/learning-paths/machine-learning/data-scientist/ https://aws.amazon.com/training/learning-paths/machine-learn... that were highly recommended. But it all comes down to what you really want. If you just want to get a bird's eye view of the ML algorithms buffet for you to implement one of their Black box models then they are a good place to start. But for anything deeper, I would go with Charlysl's recommendation.
briga 8y ago
The online Stanford courses--CS224, CS229, CS231--are an excellent introduction into modern AI. CS231 with Andrej Karpathy in particular was a game-changer for me. It has three very thorough and well-designed assignments that will have you implement many of the basic algorithms discussed in the course. The pre-requisite linear algebra for these subjects can be learned through Gilbert Strang's MIT course. A basic grounding in statistics and probability theory, along with calculus will also help.
charlysl 8y ago
To learn a solid theoretical foundation: Caltech's "Learning from data" [1]. It is one of those rare courses where the professor is so good that he manages to make tricky concepts seem almost trivial (like Paar's "Understanding cryptography"). Look elsewhere if all you want is to learn tools and start practical projects ASAP without really understanding what you are doing. Tools come and go and will serve you for a while, concepts are timeless and will serve you for life. You need both, of course, but I wouldn't skip the theory, specially when such an amazing course is on tap. [1] https://work.caltech.edu/telecourse.html https://work.caltech.edu/telecourse.html
- ultrasounder 8y ago
  Agreed! 100%. What level of math is required for the LFD course?
  - charlysl 8y ago
    Don't worry about the math, one of the great things about this course is that the professor is a magician when it comes to explaining and defanging scary looking math, you'll be fine. Having said that, it's mostly basic matrix and vector algebra, basic probability and basic calculus (all high school level).
    - ultrasounder 8y ago
      Thanks for the words of encouragement! With that said I will watch the lectures, read the book and do the assignments.
luhego 8y ago
I would recommend this course: https://mlcourse.ai/ https://mlcourse.ai/. It starts on February 11. PROS - It has a good balance between theory and practice. - There are lectures covering the theory and practice. - There are practical assignments you need to code with Python. - It includes in-class Kaggle competitions. - It includes a rating system so you can compare your progress with other students. CONS - It has some prerequisites. You need to know Python(at a basic level) and some basic knowledge of math(calculus, linear algebra, etc). - It is a difficult course. You will need between 5 to 10 hours each week for assignments. Each week is usually harder than the previous one. You can find more details in this post: https://www.kaggle.com/general/77771 https://www.kaggle.com/general/77771
source99 8y ago
fast.ai is great.

65 points by aliirz 8y ago

Ask HN: What are some of the best online resources to jump into practical machine learning

notoriousjpg 8y ago

This'd be a safe bet https://www.coursera.org/learn/machine-learning https://www.coursera.org/learn/machine-learning

sidkhanooja 8y ago

Contrary to popular opinion, I find that Andrew Ng's Intro to ML (on Coursera/Stanford) focuses too much on basic math and theory - which doesn't detract from the course's quality, but makes the course a drudgery to go through. Programming exercises involve a single line or two, and that too in Octave - which was all the rage back when the course was launched, but it's not so useful now. Instead, start with this - https://www.fast.ai https://www.fast.ai It emphasizes practicality to the extreme - you are only taught theory/domain knowledge when needed. The instructor's amazing, the massive scale of knowledge imparted boggles the mind, and you feel like you've accomplished something when you're finished with it. Best of all, it's free. And you can start Deep Learning there too when you're done with ML, if you feel the need (or interest).

k4ch0w 8y ago
I'd second this class. I have done both and if you're brand new to machine learning I'd do fast.ai first. You gain a greater understanding from Andrew's course, but if you're not going to become a practitioner fast.ai is better.
jackallis 8y ago
i have to agree with you here. It's good class if you want to focus on theory and veer towards academic part of ML.
philonoist 8y ago
There should also be some sort of polls for these sort of questions or at least for mapping goals. I past polls if any in ...yc.com/news feed. How do I go about it?
ihvck 8y ago
I really love the code first approach of Fast.ai, I'm impressed by teaching style of Jeremy its clear, succinct, and to the point.

priyanka2019 8y ago

Get over the stress of searching for a course that will be fruitful for your career. Join a Digital Marketing Course to enjoy a successful career all throughout your life. This course is in the best courses after 12th. Because this is the most progressive field which has unlimited growth opportunities and Digital Marketing alone will have 20 lakh job opportunities by 2020. Learn this course to be an expert before you complete your graduation. You can become a part of the fastest growing Industry and see your benefits grow with every passing year. Since this field is broad, you can select your profession according to your interest. There are many posts available in Digital Marketing Field- 1. SEO Executive 2.Social Media Marketer 3.Content Writer 4.Community Manager 5.PPC Executive 6.Email Marketing Executive 7.Web Designer 8.Graphic Designer 9.Digital Sales Expert 10.-commerce Marketing Manager This is one of the least unfolded pitch in India. So, this field has a huge scope to grow in. I will suggest higher studies in Digital Marketing Course. Because that can take you very high, you can work for leading companies and you can get a really handsome amount of salary. Read more at https://iiadm.in/courses-after-12th https://iiadm.in/courses-after-12th

UsernameTaken5 8y ago

There's a free intro course here: https://www.udemy.com/machine-learning-intro-for-python-developers/ https://www.udemy.com/machine-learning-intro-for-python-deve...

jackallis 8y ago

This depends upon you first telling us at what level you are? beg, int, ad.

cromiium 8y ago
Not OP but I'm a beginner. Any recommendations different than what was already said?

solomatov 8y ago

This one: https://see.stanford.edu/course/cs229 https://see.stanford.edu/course/cs229 It's a recording of CS229 at Stanford. This course is much harder and more thorough than the one on coursera.

nwsm 8y ago

Udemy's Machine Learning A-Z course: https://www.udemy.com/machinelearning/ https://www.udemy.com/machinelearning/ All lessons in R and Python. Wide range of content.

Isamu 8y ago

Google ML crash course: https://developers.google.com/machine-learning/crash-course/ https://developers.google.com/machine-learning/crash-course/ Facebook field guide to machine learning: https://research.fb.com/the-facebook-field-guide-to-machine-learning-video-series/ https://research.fb.com/the-facebook-field-guide-to-machine-... Training on Machine Learning with AWS: https://aws.amazon.com/training/learning-paths/machine-learning/ https://aws.amazon.com/training/learning-paths/machine-learn...

simple_phrases 8y ago
Can anyone comment on whether these are worth the time investment versus more traditional courses?
- ultrasounder 8y ago
  I haven't taken any of these courses. There were these courses from Amazon https://aws.amazon.com/training/learning-paths/machine-learning/data-scientist/ https://aws.amazon.com/training/learning-paths/machine-learn... that were highly recommended. But it all comes down to what you really want. If you just want to get a bird's eye view of the ML algorithms buffet for you to implement one of their Black box models then they are a good place to start. But for anything deeper, I would go with Charlysl's recommendation.

briga 8y ago

The online Stanford courses--CS224, CS229, CS231--are an excellent introduction into modern AI. CS231 with Andrej Karpathy in particular was a game-changer for me. It has three very thorough and well-designed assignments that will have you implement many of the basic algorithms discussed in the course. The pre-requisite linear algebra for these subjects can be learned through Gilbert Strang's MIT course. A basic grounding in statistics and probability theory, along with calculus will also help.

charlysl 8y ago

To learn a solid theoretical foundation: Caltech's "Learning from data" [1]. It is one of those rare courses where the professor is so good that he manages to make tricky concepts seem almost trivial (like Paar's "Understanding cryptography"). Look elsewhere if all you want is to learn tools and start practical projects ASAP without really understanding what you are doing. Tools come and go and will serve you for a while, concepts are timeless and will serve you for life. You need both, of course, but I wouldn't skip the theory, specially when such an amazing course is on tap. [1] https://work.caltech.edu/telecourse.html https://work.caltech.edu/telecourse.html

ultrasounder 8y ago
Agreed! 100%. What level of math is required for the LFD course?
- charlysl 8y ago
  Don't worry about the math, one of the great things about this course is that the professor is a magician when it comes to explaining and defanging scary looking math, you'll be fine. Having said that, it's mostly basic matrix and vector algebra, basic probability and basic calculus (all high school level).
  - ultrasounder 8y ago
    Thanks for the words of encouragement! With that said I will watch the lectures, read the book and do the assignments.

luhego 8y ago

I would recommend this course: https://mlcourse.ai/ https://mlcourse.ai/. It starts on February 11. PROS - It has a good balance between theory and practice. - There are lectures covering the theory and practice. - There are practical assignments you need to code with Python. - It includes in-class Kaggle competitions. - It includes a rating system so you can compare your progress with other students. CONS - It has some prerequisites. You need to know Python(at a basic level) and some basic knowledge of math(calculus, linear algebra, etc). - It is a difficult course. You will need between 5 to 10 hours each week for assignments. Each week is usually harder than the previous one. You can find more details in this post: https://www.kaggle.com/general/77771 https://www.kaggle.com/general/77771

source99 8y ago

fast.ai is great.