I highly recommend https://course.fast.ai/ . It's much more top down: in the first lesson or two, you train a NN image classifier, rather than starting with first principles and linear algebra. I found this structure to be more motivating and effective.
Fast AI teaches you a little bit more about being a practitioner, dealing with datasets, pointing the right algorithms at the right data and checking whether you get good results.
Andrew Ng for me did a lot more to demystify how stuff actually works
Although this is the best course on ML, is it really practical for anything? Has anyone built products for things they’ve learned from this course?
No. The ugly truth is that these courses will be useless to 99% of the people. Machine learning is dominated by big corporations with gigantic amounts of data and processing power. If you want to work in one of them or create competing ML companies you need pedigree (a PhD from a well know university), and those guys arent taking courses with fake credentials. You could use ML in your job/company but then you dont ne…
You can get almost unlimited GPU time on Google Colab for $50 a month. I don't know why or how they pay for this, but it does bring "real research" into the reach of individuals.
I didn't do these particular courses but I found it a lot easier to stay motivated with the top down approach. First demonstrate usefulness, then deepen fundamentals. When I was younger and didn't work full time + have other commitments the bottoms up approach appealed to me more, I think partially because I had bigger time blocks to allocate. i.e I could spend a whole weekend just learning fundamentals of some parti…
> When I was younger and didn't work full time + have other commitments I second this - while both are great courses, I found I could only dedicate very short amounts of time recently to any kind of study, and going from the ground-up more thoroughly seemed like I was making no progress. The fast.ai top down approach worked a bit better for me for those reasons, otherwise it would have been interesting starting with…
Yeah, this is probably the reason it worked better for me as well. I had bounced off of some other courses because I didn't have the time to dedicate 16+ hours of lectures before I would get to the fruit of all that foundational knowledge. Starting with some high-level abstractions, then digging down into how each of those abstractions ticked, kept the number of concepts I had to remember at once to something more manageable while dealing with distractions like a full-time job.
All videos of all courses in Coursera are free. You can watch them fully without providing your credit card info. There are two types of courses in Coursera- free and paid. In case of the paid courses, you can go to the course and navigate to the "Buy Subscription" page and click on "audit the course". You can watch all the videos for free, but you don't get access to quizzes and programming assignments (you never kn…
> All videos of all courses in Coursera are free > There are some great courses in the full free tier as well. So the full free tier courses offer a free certification? Or else what would be the difference?
They give you access to assignments. For Andrew's courses it gives access to Jupyter server to run your codes.
All videos of all courses in Coursera are free. You can watch them fully without providing your credit card info. There are two types of courses in Coursera- free and paid. In case of the paid courses, you can go to the course and navigate to the "Buy Subscription" page and click on "audit the course". You can watch all the videos for free, but you don't get access to quizzes and programming assignments (you never kn…
> All videos of all courses in Coursera are free > There are some great courses in the full free tier as well. So the full free tier courses offer a free certification? Or else what would be the difference?
Though I had almost zero ways I would actually use the learning from this course (and indeed really never did any ML after and have probably forgotten it all) it was still a really fun brain exercise to revisit some math and then see how ML thinking worked! I have recommended it quite a few times.
Not a full course I'd say, but I've used this one to learn the math behind deep neural networks and code my own from scratch in elixir and C: http://neuralnetworksanddeeplearning.com/
No. The ugly truth is that these courses will be useless to 99% of the people. Machine learning is dominated by big corporations with gigantic amounts of data and processing power. If you want to work in one of them or create competing ML companies you need pedigree (a PhD from a well know university), and those guys arent taking courses with fake credentials. You could use ML in your job/company but then you dont ne…
You can get almost unlimited GPU time on Google Colab for $50 a month. I don't know why or how they pay for this, but it does bring "real research" into the reach of individuals.
You can get more processing power and true unlimited time with any semi-competent graphic card (probably costing less than 1 year of Colab Pro+). Pro+ is a scam, you are not told what kind of instances you will be running at, and you dont have any guaranteed continuous running time. And even if you were given full 24/7 access to a top of the line card that would be like 0.001% of the power used to train any big modern ML model.