The Mathematics of Machine Learning

48 thoughts on “The Mathematics of Machine Learning”

1. How to prevent overfitting?

2. 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.

3. 3:16 if you know that the function is parabolique, why you don't use -b/2a for found the minimum of that function?

4. Bra sounded heated at 0:47 secs about something wonder what it could be lol

5. Yes instant like, you if YouTube if you read comments based on views show me more videos about machine learning videos thank both of you

6. Superb explanation sir! I'm glad atleast some people are doing the job of spreading knowledge free of cost…. 😊

7. What the fuck this is literally Stanford's intro to ml

8. Make videos for ML beginners please. This video is excellent.

9. he looks and speaks like dustin in stranger things

10. This is baby talk. Look up Sebastian Bubeck and then even utter the word math.

11. Neural nets are just 1 type of machine learning algo's

12. Did nobody else find the "linear/nonlinear" joke hilarious?

13. part 2 please: where exact we apply algebra, matrix algebra, calculus, stats into a specific ML application ? That would be just great !

14. dude, I love you your intelligence

15. This stuff and lots of science and mathematics would be easier to understand if the teachers of it were not pretentious idiots that make it seem even more complex than it is

16. That you make is not so Hard. I make program that recognize handwriten digit on c#. Convolutional neural network are hardcore. They have convolutional layer, pool layers, relu layers, fully conected layer which you show. Please make video for them

17. looks ez will try to learn it

18. You're amazing bro

19. I believe the equation m(new) = m(current) – k(dE(m)/dm) is kown as "Newton's methode" for finding the zero of function f(x), in this case f(x) is just the derivative of the parabola he plotted.

20. Excellent video

21. Are you using python ??

22. Can I learn ai and self driving car from coursea

23. For those of you that do not know calculus, LEARN CALCULUS! It will change the way you see the world!

24. Wow visualisation helped me a lot to understand sigmoid function better

25. I found your explanation way more comprehensible than 3 blue 1 Brown's series on the topic.

26. Guhvcfg

27. So informative. Covers lot of basic starts

28. thanks to andrew NG hhhhh

29. After watching this video if any beginners wants to learn more about math in machine learning I would like to recommend Andrew Ng's Coursera course also available in Youtube.

30. MachinLearning 2020!

31. sir please tell me what software your using for graph and baubles

32. I really wanted to learn coding/machine leatning, now I just don't know 🙁
    Help!

33. Best Explanation about gradient descent

34. Where is part 2?

35. I wouldn't come here if I were first grasping the concepts. The methods are too complicated and need to be learned rather than listening to another overly simplified 15 minutes video. Good luck everyone.

36. https://youtu.be/Yuy4efF-QMQ

37. thanks broo greetings from colombia pereira capital del eje.

38. The music is too distracting.

39. 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.

40. 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.

41. Now I'm a big fan of Zach 🌟. 💜💜💜💞💞💞

42. Amazing content….Very beautifully and efficiently provided the intuition behind the algos

43. 🔵 Make more videoa on this topic IA, neuro network please, the video is awsome

44. I got confused about why he plugged the obtained (1.2139) value into sigmoid function to find passing percentage.

45. let's make a guess and fit it by a parabola for no apparent reason, right, that's what we do to understand it…

46. Machine learn k maths nahi hai primary school k hai

47. Is there anyway possible on a compurter.9

48. Please do a second video, very interesting!

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