My Favorite Calculus Resources - Topic 92 of Machine Learning Foundations
HTML-код
- Опубликовано: 10 сен 2024
- #MLFoundations #Calculus #MachineLearning
This is the final calculus video of my Machine Learning Foundations series. In it, I leave you with my favorite external calculus resources and wrap a bow on this subject area.
There are eight subjects covered comprehensively in the ML Foundations series and this video is from the fourth subject, "Calculus II: Partial Derivatives & Integrals". More detail about the series and all of the associated open-source code is available at github.com/jonkrohn/ML-foundations
The playlist for the Calculus subjects is here: • Calculus for Machine L...
Jon Krohn is Chief Data Scientist at the machine learning company Nebula. He authored the book Deep Learning Illustrated, an instant #1 bestseller that was translated into seven languages. He is also the host of SuperDataScience, the industry’s most listened-to podcast. Jon is renowned for his compelling lectures, which he offers at Columbia University, New York University, leading industry conferences, and online via O'Reilly.
More courses and content from Jon can be found at jonkrohn.com.
finally I completed this calculas series . thank you Dr. Jon Krohn ❤
Just wanted to thank you for that awesome calculus course Dr. Krohn. You are a truly gifted teacher and I am very lucky to have come across your videos. I will be watching the rest of your content through O'Reilly! Thanks again!
Awesome, Talha - so glad you enjoyed the course! And you're most welcome - I appreciate your kind words :)
Addicted with your teaching. Excellent flow, awesome explanation, very neat and clean. No words to say. You're god gifted teacher to us. Now I 'm confident in maths. Thank you so much sir 😊
Did you study the algorithms as well from Oreilly or went directly to data analysis Pandas,numpy , matplot
I cannot describe my gratitude for these videos Jon - thank you so very much. I have only a limited maths background but wanted to better understand the papers in the ML/DL space for my PhD. I came only for the calculus, but thoroughly enjoyed the linear algebra and will be watching the rest of your videos in this series. The maths could not have been explained more clearly; the ML applications keep the big picture in mind and help you connect with the maths; the code examples are illuminating; you dwell exactly the right amount of time on the more difficult concepts. This has been a masterful display in the education of complex issues. You've completely changed my understanding of the ML/DL space for the better. You're brilliant mate - thank you.
Rhys, mate! You've actually made my day. Nothing is more encouraging to me than hearing that my content resonates with you in the way I was hoping it would. I'll be recording more Probability, Stats, and Computer Science content soon! If you'd like to be sure to get a notification when I start releasing new videos again, you can sign up for my email newsletter on jonkrohn.com
@@JonKrohnLearns Amazing. Thank you! I've signed up to your newsletter. You make the days of a bunch of people mate when they can understand this stuff because of you even if they don't say so. Thanks again
And just purchased your text book. It's so good!
@@rhysm8167 ah man, thanks so much for saying that :)
@@rhysm8167 sa-weeeet! I can't wait to get my "Mathematical Foundations of ML" book out!!!
I believe studying calculus from alternative resources poses a significant challenge, especially as I've recently begun my mathematical journey. When attempting to comprehend other textbooks or articles, I struggle with understanding symbols, their meanings, and other cryptic elements.
Hence, I kindly request recommendations for beginner-friendly resources, such as the book "Calculus Made Easy." Can you also advise if it's suitable to study reference resources?
This was the most underrated course for ML math ever! I've been an AI hobbyist for a few years now and studied the math from a lot of different sources but this one was the course that crystallized it all and made me confident with it all. You are a very gifted teacher. I see that other subjects are still a work in progress under youtube. For now, how do you suggest we proceed until rest of the youtube work is done? Your Udemy course ends with a probability chapter, and I believe you also have some O'Reilly stuff that cover these. Just hungry and want to proceed, so any suggestions?
Thank you for the positive feedback! Genuinely means a ton to hear it :)
I'm eager to continue making this course content for RUclips but have been overwhelmed by other projects (my ML company, Nebula, and my podcast) recently.
You're right that the Udemy videos are released roughly in parallel with RUclips so sadly more content isn't yet there. The entire course is, however, available via O'Reilly today. They have a seven-day free trial so maybe that's enough time to plow through my Prob, Stats, and CS material?
Something went *wrong* with me.
I completed the playlist for the Calculus II subject. Two days ago, I finished my exams, and I don't know why during my holidays, I studied hard to complete the rest of the course.
Thanks Jon :D
thx
@JonKrohnLearns John! You are truly a life saver. This ml foundation serie is top notch. I just want to ask that these linear algebra and calculus topics are enough for ml or we have to learn more?
Hi Ahmad! I wish there was a simple answer to this question. My LinAlg and Calc videos on RUclips cover the most essential topics for ML, but it can't hurt to learn even more if you have the time or interest. That's why I provide my favorite resources in this video :)
aaaaan done!
thank you so much John!
hey Jon, I'm a Computer Science Fresh Graduate, Junior Android Developer Planning to complete my Studies - Signing up to Artificial Intelligence and Robotics master degree, should I start with the linear Playlist ? or I should start learning from a data science course ? also I know how to program with python It's Easy for me
Hey Ahmad! Since you have a Python background, you're good to start with the Linear Algebra playlist - lemme know how it goes :)
@@JonKrohnLearns I really Appreciate your Efforts and wish your channel reach Millions of Viewers!
Hi John this is great stuff. I don’t have a coding background and need a refresher in math for ML. Would your playlists help bridge that gap and where can I start ?
Hi Aalekh - Glad you're enjoying my stuff! If you start from the beginning of my "Linear Algebra for ML" RUclips playlist, we do begin with some relatively simple coding: ruclips.net/p/PLRDl2inPrWQW1QSWhBU0ki-jq_uElkh2a
When we do something in the video that you don't understand, then Google it! You'll gradually start to fill in the gaps. Alternatively, you might want to work through a Python book either first or in parallel. Here's a good (and free!) option: automatetheboringstuff.com/