@camozot
This is the best quick explanation of machine learning I have seen to date. You covered the first few weeks of the course extremely well and concisely. I shared with all my friends to get them more hyped about machine learning!
@alanbouwman5627
The subtle "used to demonetize your favorite videos across this entire platform." Savage
@galenseilis
With gradient descent, we generally don't update one parameter and 'then' another. Rather, parameter updates are done simultaneously. Great video overall. I like how you started with a simple model structure and skipped the derivations to keep things understandable to a broader audience.
@giorgospap7615
This is probably the most explanatory video I've ever seen for a beginner. Please continue making more videos about the mathematics of machine learning and how they're applied
@nahomdagnew9209
This topic is explained in depth in Linear algebra.
@gerrychen
Toward the end of the video, I think an important note to make is that multilayer neural networks need some sort of activation function (i.e. ReLU) to be considered nonlinear. The sum of a bunch of linear weight multiplications is still linear so the activation is required to make it nonlinear. I think this is especially important to note because the neural networks were explicitly introduced as a way to make machine learning nonlinear. Good video!
@jackfitzpatrick6863
This is a great explanation of a very complex subject. While incorporating and utilizing such a topic doesn't require an intense understanding of the process, it does help to share the facts with others.
@projectjt3149
I already took the Coursera course, but BOI was this a good refresher. Also helps me as a CS major have a clearer idea of what math I'll need to take. Thanks again!
@pratyusharavishankar5573
Hey it would be great if u could do a machine learning course for complete beginners, here on YouTube. I really enjoyed this vedio! Thanks you so much for this!!
@Slecker95
0:46 OMG that burn!!!
@Kevin-cy2dr
Dude how did you read my mind?i really needed this video..Thanks a lot
@rohank9292
Thankyou so much for making this video giving a gist of the mathematics behind machine learning, and getting me excited about undergoing courses in this field.
@user-mo8mg4ks9h
Nice video! Hands down your channel has delivered the most useful information to me and my future. Not to mention interesting videos like this one. I've been doing discrete math stuff and so it's refreshing to learn about more continuous and applied math concepts.
@ankitnmnaik229
Hard reality - the harder and complex the project is the more math (a better and efficient solutions) is needed,so you do need math ...the more you know about math and actually imp part is how to apply them in your problem.. So good part is that we can learn mathematics through practice.. I myself is not good at math ,but i will learn it by giving a great deal time and concentration.. I am ready for it ..I won't scared because of math.. 😤😤
@amitjose3739
Im glad i discovered both your tech and your comedy channel. The only regret I have is not discovering these earlier. Thank you for the content.
@anacamargos2894
Excellent video. More precise and enlightening than many MOOCs out there.
N/A
Sigmoid functions are a group of functions that have an S-like curve and arcus tangent and even signum function are sigmoid functions. The f function in the video is just one of the possible sigmoid functions called logistic function.
@akwotom9144
Merçi. Thanks for taking the time to show us the basics.
@m10al
I have master of science in hydraulics and you explained most of this stuff way better that my profs back then. 10/10
@ducodarling