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Plotting a System of Linear Equations - Machine Learning Foundations Bonus Video
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- Опубликовано: 31 янв 2021
- In this video, we recap the sheriff and robber exercise from the preceding video, now viewing the calculations graphically using an interactive code demo in Python.
There are eight subjects covered comprehensively in the ML Foundations series and this video is from the first subject, "Intro to Linear Algebra". More detail about the series and all of the associated open-source code is available at github.com/jonkrohn/ML-foundations
The next video in the series is: • Linear Algebra Exercis...
The playlist for the entire series is here: • Linear Algebra for Mac...
This course is a distillation of my decade-long experience working as a machine learning and deep learning scientist, including lecturing at New York University and Columbia University, and offering my deep learning curriculum at the New York City Data Science Academy. Information about my other courses and content is at jonkrohn.com
Dr. Jon Krohn is Chief Data Scientist at untapt, and the #1 Bestselling author of Deep Learning Illustrated, an interactive introduction to artificial neural networks. To keep up with the latest from Jon, sign up for his newsletter at jonkrohn.com, follow him on Twitter @JonKrohnLearns, and on LinkedIn at linkedin.com/in/jonkrohn
John, honestly, I have watched dozens of youtube videos that cover Linear Algebra and by far you're the best! The way you break down the problem is amazing and not to forget the way you simplify the equations is great!
Nothing makes me happier than to hear feedback like this, Nawaz! Truly I'm honoured that you feel this way. I will do my very best to continue publishing videos to the high standard that you've come to expect from me :)
I am also feeling so!
Tnx John
@@mdminhajtahertitu8946 delighted to hear it - thank you!
Wow, that's how teaching should be done. Loved the way you taught. Respect ++
You are a great teacher, John. No words can suffice to express my gratitude ❤
Awww so nice to hear this, Yousef. You are so very welcome :)
Great video! Your teaching style is amazing. You have a talent for making complex mathematical concepts easy to understand. Thank you for sharing your knowledge with us. Keep up the excellent work!
Ah, thank you and you're very welcome!
Where have you been all my life🤣💜💜. All these course materials is worth thousands of dollars out there and the fact that you are giving knowledge out for free is unbelievable.
Please don’t stop until all the series are completed.
Awesome lectures!!!!
I'm glad you're enjoying these materials so much! And, yes, I will publish my entire ML Foundations series on RUclips :)
@@JonKrohnLearns Do you plan on compiling all of this into one book, potentially titled ML Foundations?
@@RainnFTWj right now I'm working on a book version for the linear algebra and calculus parts of my "ML Foundations" curriculum that is called "Mathematical Foundations of ML". After that, I plan to start on books that also integrate the probability, stats, and computer science content as well.
@@JonKrohnLearns Your hard work is inspiring. Kudos to you! You are helping everyone.
Thank you! I should have mentioned yesterday: If you'd like to be sure not to miss any updates on my content, you can sign up for my email newsletter on jonkrohn.com
This is the best channel ever. I never known until I reach this channel. Now, I understand the beauty of Math and Python when they combine together in practice. Thank you so much, Jon Krohn. This is the best channel for me ever. 😍
❤ this is what I was looking for.
As a Satellite Navigation Scientist, I have to master every single bit of concept in linear algebra and calculus.
Dr. John thank you so much for this wonderful effort. I am starting my own PhD journey. Do let me know if you are interested in research collaboration in GNSS based natural hazards monitoring
I'm thrilled to hear that my content has been helpful to you, especially as you embark on your PhD journey. Your field of study sounds fascinating and I wish I could make time to collaborate on another exciting project!
@@JonKrohnLearns thank you so much and please don't stop the good work that you are doing right now
This was a great video. You made it sound really approachable and easy.
amazing series for ml
Cheers, Vipul :D
This is an amazing series. Thank you
Nice, Richard! I'm delighted you think so :)
Excellent.. thanks for all your great effort
🎉You are the best teacher❤
God bless you Jon.
This may sound weird, but the idea that we generate a spectrum (time) with an arbitrary sample rate and scope. [2] And then merge a concept into the spectrum to yield a photo of the result.. [3] Is awesome. Saw that you're into philosophy, so hopefully you sense what i'm trying to say.
@JohnKornLearns is it important to learn python language before continuing this playlist
I cover some of the essential Python for ML but generally it might be a little hard to follow along. The good news is that you can now use a tool like ChatGPT's GPT-4 algorithm to simply ask it for guidance on any of the code examples I have that you don't understand 100%.
Your videos are amazing
thank you so much for these videos..
You're most welcome, Finn! Thanks for watching :)
Thank you for your videos!
Of course, Faith! Thank you for watching them :)
Ok for this video are we supposed to type those lines of code for practice or just watch to have an overview of it? I am bit confused.
Also I come from biology background and have never written a line of code and have read mathematics around 16 years ago. In that case these video series is going to be helpful for me?
I appreciate anyone's inputs.
TIA
Thanks, Jon; I have a question: If I said d_s = 3t and d_r = 2.5(t+5), so the accurate time the sheriff needs to catch the bank robber is 25 min because the first 5 minutes his distance is 0, Is that wrong thinking?
both counts will equal to 75km, but I also thought that maybe he missed out a little in the previous video. In my opinion, The robber is 5 minutes ahead, so the total time the robber traveled should be 30 minutes, since the sheriff is 5 minutes late, the sheriff should have traveled 25 minutes to catch the robber. Its logic, if sheriff takes 30 minutes to catch the robber, then the robber should have traveled 35 minutes, and that would be the point the robber gets caught.
Does your udemy course, Mathematical Foundations of Machine Learning, cover the basics or is it at a more intermediate level?
Great question! It starts with the basics and then works its way to an intermediate level. You can get an overview of the whole curriculum from the GitHub repo here: github.com/jonkrohn/ML-foundations
I really don’t want to enter code onto Python, but I also really want to understand how neural networks though. So I might force myself to do an excercise lol 😅
completed this using Python
Same as in the video or a different approach?
@@JonKrohnLearns verbatim As explained in the video . Is there ay other approach :-)
haha I suppose there are infinite approaches in infinite programming languages! I'm glad my approach worked for you :)
doing a great work and make it so easy to understand ..thank you
So happy to hear it, Taruna - you're most welcome :D
Can anyone tell me where do we learn the python? I can't understand the plot making with the codes, can't define each of the code meaning.
I can't find the series now..is it available?
Yep! It's all available. All of my series are featured on my RUclips profile. For quick access, my Linear Algebra playlist is here: ruclips.net/p/PLRDl2inPrWQW1QSWhBU0ki-jq_uElkh2a
Sir , why can't i use your code on python ?
I did not understand 2.5t and why t has to be 1000 points between zero and fourty.
The 1000 points is arbitrary; later when we plot curves, not just straight lines it will be helpful to have some sort granularity to the curve. You can optionally make it 10,000 or 100,000 points or more if you want more and more granularity, but 1000 seems plenty!
I picked 0 and 40 to define a range that I knew would be broad enough to see the most interesting parts of the line in a chart.
@@JonKrohnLearns Oh, alright. Thanks for the clarification. Great video series btw, please continue doing more.
@@magmacodes9143 planning on getting back to my weekly new-RUclips-video releases starting this autumn! You can sign up for my email newsletter on jonkrohn.com to be sure not to miss when I start uploading them again.
@@JonKrohnLearns Sure thing !
Voice is very low
Thank you. These videos are so helpful. 🤍