HOLYYYYY GWAKAMOLE !!!! I really wish I came across your video much before I took the painful ways to learn all this… definitely a big recommendation for all the people I know who just started with optimization courses. Great work !!!!!
Thank you Ahmad for this amazing tutorial video you have made. I am a researcher and work on large datasets. Basically, I am a wet lab scientist but really want to python to write different codes that will help me analyze the huge dataset. When I started working with large datasets I did all the calculations and sorted the data manually which is so labor intensive. Therefore, python will certainly help me in minimizing my efforts and provide more robust data analysis power.
Hi Ahmad! A big thank you from India. I am an engineer in material science from last 6 years and never learnt any programming language to be frank and today I am starting my Python journey in a quest to enter in to the field of machine learning and artificial intelligence for simulation of advanced materials. You have made this course super easy for the zero beginners like me. Hopefully I will complete this course and then will proceed to Python mastery course. And happy teacher's day.
This course has literally changed my life. 2 years ago i started learning optimization from this course and convex optimization from Ahmad's famous course and now i am a research scientist at a great research institute. Thanks Ahmad♥️
Gorgeous tutorial ! I have never even saw the pyhton interface in my life before, but with the help of your videos i feel like i understand a lot. Also, when you let us try with the 'homework' that`s where the experience shows. my code is always longer and less intuitive. also, i seem to opt for the input command a lot more. something about interracting with the code always gets me !
I love this video, I feel so privileged to be growing up in an era where knowledge is so easily available, Ahmad is really helping to improve my and many other's opportunities.
Excellent video. I especially liked how you linked it back to the root finding version we learned in school. My one beef with this video is that that's an unfair depiction of Tuco.
Hello, great video. I am currently following a course on non-linear optimization and I would like to make videos like this for my own problems. I'm a visual learner and this video is exactly what I'm looking for! Great content!
Hi Ahmad. Thank you so much for putting this together. I’m wanting to learn python because I’m a teacher with an IT background who wants to find a way to make simple web applications to make life easier for my fellow teachers. I’m mostly interested in creating a way for teachers to enter data (assessment data, house points etc), which can then be collated, summarised and displayed in useful ways.
After 2.5 years, I am returning here to say that I’ve just accepted a job offer for a good salary, and my IT journey started here, from this video, in November of 2019. This was my first source of information, when I got back from work (being a cable tech), and typed “Python full course” or something along those lines. Of course, back then, a lot of concepts like classes and inheritance meant nothing to me, and this video perhaps wasn’t the most beginner friendly. However, I was so sick of my job and I absolutely saw no growth in doing cable, where the salary cap for a technician was probably IT jobs base pay for the most part, so I decided to Google every single thing I don’t understand. And I successfully changed careers.
It's rare when less viewed video gives best explanation. Your presentations are almost like 3Blue1Brown or Khan academy! Don't know why this video has this less view!!
Sure. Consider the quadratic approximation f(x) ~ f(xk) + f'(xk) (x - xk) + 1/2 f''(xk) (x-xk)^2 at the bottom of the screen at 7:06. To minimize the right hand side, we can take the derivative with respect to x and set it to zero (i.e., f'(xk) + f''(xk) (x - xk) = 0). If you solve for x, you get x = xk - 1 / f''(xk) * f'(xk).
Another problem is for a negative curvature, the method climbs uphill. E.g. ML Loss functions tend to have a lot of saddle points, which attract the method, so gradient descent is used, because it can find the direction down from the saddle
HOLYYYYY GWAKAMOLE !!!! I really wish I came across your video much before I took the painful ways to learn all this… definitely a big recommendation for all the people I know who just started with optimization courses. Great work !!!!!
Thank you Ahmad for this amazing tutorial video you have made. I am a researcher and work on large datasets. Basically, I am a wet lab scientist but really want to python to write different codes that will help me analyze the huge dataset. When I started working with large datasets I did all the calculations and sorted the data manually which is so labor intensive. Therefore, python will certainly help me in minimizing my efforts and provide more robust data analysis power.
Hi Ahmad! A big thank you from India. I am an engineer in material science from last 6 years and never learnt any programming language to be frank and today I am starting my Python journey in a quest to enter in to the field of machine learning and artificial intelligence for simulation of advanced materials. You have made this course super easy for the zero beginners like me. Hopefully I will complete this course and then will proceed to Python mastery course. And happy teacher's day.
This course has literally changed my life. 2 years ago i started learning optimization from this course and convex optimization from Ahmad's famous course and now i am a research scientist at a great research institute. Thanks Ahmad♥️
It just needs more videos to get rocket growth !! Very Good Quality stuff ..
This is so high quality stuff! Thanks for the graphical explanation at the beginning!
Gorgeous tutorial ! I have never even saw the pyhton interface in my life before, but with the help of your videos i feel like i understand a lot. Also, when you let us try with the 'homework' that`s where the experience shows. my code is always longer and less intuitive. also, i seem to opt for the input command a lot more. something about interracting with the code always gets me !
I love this video, I feel so privileged to be growing up in an era where knowledge is so easily available, Ahmad is really helping to improve my and many other's opportunities.
Excellent video. I especially liked how you linked it back to the root finding version we learned in school. My one beef with this video is that that's an unfair depiction of Tuco.
WoW! This is amasing work man, thank you.
This is brilliant thank you, hope you give us more visual insight into calculus related things
Amazing explaination! This is very helful for understanding. Thanks a lot sir.
Hello, great video. I am currently following a course on non-linear optimization and I would like to make videos like this for my own problems. I'm a visual learner and this video is exactly what I'm looking for! Great content!
Hi Ahmad. Thank you so much for putting this together. I’m wanting to learn python because I’m a teacher with an IT background who wants to find a way to make simple web applications to make life easier for my fellow teachers. I’m mostly interested in creating a way for teachers to enter data (assessment data, house points etc), which can then be collated, summarised and displayed in useful ways.
After 2.5 years, I am returning here to say that I’ve just accepted a job offer for a good salary, and my IT journey started here, from this video, in November of 2019. This was my first source of information, when I got back from work (being a cable tech), and typed “Python full course” or something along those lines. Of course, back then, a lot of concepts like classes and inheritance meant nothing to me, and this video perhaps wasn’t the most beginner friendly. However, I was so sick of my job and I absolutely saw no growth in doing cable, where the salary cap for a technician was probably IT jobs base pay for the most part, so I decided to Google every single thing I don’t understand. And I successfully changed careers.
Loved the graphical presentation
Thank you for your amazing comment :-)
Crystal clear explanation, thank you!
This was such an awesome explanation, so grateful thank you.
It's rare when less viewed video gives best explanation. Your presentations are almost like 3Blue1Brown or Khan academy! Don't know why this video has this less view!!
Brillant explanation, thank you so much.
Thank you for the words of encouragement, I appreciate it!
Sure. Consider the quadratic approximation f(x) ~ f(xk) + f'(xk) (x - xk) + 1/2 f''(xk) (x-xk)^2 at the bottom of the screen at 7:06. To minimize the right hand side, we can take the derivative with respect to x and set it to zero (i.e., f'(xk) + f''(xk) (x - xk) = 0). If you solve for x, you get x = xk - 1 / f''(xk) * f'(xk).
Another problem is for a negative curvature, the method climbs uphill. E.g. ML Loss functions tend to have a lot of saddle points, which attract the method, so gradient descent is used, because it can find the direction down from the saddle
Great content
Great video man. God bless you
you are tooo much underrated :(
Amazingly presented, thank you.
This is great.
Good job. I am subscribing !
can someone please tell me whats the algebra needed for getting the newton method from the taylor series stated in 6:58. thank you in advance
Awesome, thank you!
Amazing job! Thanks a lot!!
oh man is this gold
Thanks a lot 😊
amazing
What is the plotting tool you are using?
Yayy!
Hey can you do a sum of square, dsos optimization tutorial for post graduate student.
Or did you mean i.e. an abbreviation for 'that is'.
Who do you think is the created scientist who ever lived?
you reading out the whole things made things confusing.
Me a Hindu 30 seconds after 5:42- Oh no! THIS SHOULDN'T BE COINCIDING!!!!!
I have explained this in another comment. Let me paste it here:
Jesus Christ is the most influential man and God of all time
Make no mistake God Almighty gives his children what HE wants us to have. For HIS purposes to increase Knowledge before HIS coming.
i am sad
Great content