Logistic Regression in 3 Minutes
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- Опубліковано 17 вер 2022
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Essential Math for Data Science
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Getting Started with SQL
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In this 3-minute video, we cover logistic regression which is helpful for predicting probability and classification given one or more input variables.
Animation source code:
github.com/thomasnield/3mds/b...
This video has been inspired by 3Blue1Brown, and special thanks to Grant Sanderson and the ManimCE community.
Follow me on LinkedIn for posts and updates. Reach out to me for questions, I'm busy but I don't bite.
/ thomasnield
Music used
Road Less Travelled by Jonny Easton
Link: • Road Less Travelled - ... - Наука та технологія
![Logistic Regression [Simply explained]](http://i.ytimg.com/vi/C5268D9t9Ak/mqdefault.jpg)
![Logistic Regression [Simply explained]](/img/tr.png)
To support more videos like this, please check out my O'Reilly books.
Essential Math for Data Science
amzn.to/3Vihfhw
Getting Started with SQL
amzn.to/3KBudSY
Access all my books, online trainings, and video courses on O'Reilly with a 10-day free trial!
oreillymedia.pxf.io/1rJ1P6
I'm grateful that people like you carrying the work Grant started. One person can only do so much, but I'm sure people like you will revolutionise maths learning in the future with ever-growing topics covered.
concise, clear and under 4 minutes. bravo and thanks for your work!
I recently discovered that this is the Thomas Nield channel, and I must express my admiration. Your book, "Essential Math for Data Science," has been invaluable to my learning journey. Sir, your work is amazing, and I look forward to watching more of your videos. Please continue inspiring us with your expertise.
Good day, how can i get this book pls
Thank you! It means a lot it helped you. And @boluwatifeadebowe1427 you can get the books here:
Essential Math for Data Science
amzn.to/3Vihfhw
Getting Started with SQL
amzn.to/3KBudSY
You can also access all my books, live online trainings, and video courses on O'Reilly.
oreillymedia.pxf.io/1rJ1P6
Your videos are so well made.
Thank you! Using this to refresh the mechanics behind some methods for my data analytics course. Short, but powerful video.
This video could help you out too:
Another great video about logistic regression in JMP
ua-cam.com/video/9yN_yjGAJZE/v-deo.htmlsi=jUwEZUDobBudE8AE
bravo - well done
Thank you very much.
Very well made video! Reminds me of 3 blue 1 brown
Grant’s work was definitely an inspiration for this series! And thank you
@@3-minutedatascience also Manim is in use here am I right? Loved the video btw!
@@nfiu Yes, these videos use Manim
Thanks for this video! I like the visual graphics and the voice 😀
Another great video about logistic regression in JMP
ua-cam.com/video/9yN_yjGAJZE/v-deo.htmlsi=jUwEZUDobBudE8AE
I love this video keep going :D
You could like this video too:
Another great video about logistic regression in JMP
ua-cam.com/video/9yN_yjGAJZE/v-deo.htmlsi=jUwEZUDobBudE8AE
Hello, nice video ! how did you classifier in 2 perfects lines ? My hypothesis is that : Lets say you have 2 features : weight and height, you place them in a 2D plan. Then, you find a decision boundary, and give the decision boundary, you predicts all these points and then given the distance of each point and the decision boundary, you place them in the sigmoid function. Is it right ?
If not, can you explain me briefly how we do that ? Because I'm but confused about what we optimize : In the video you explain that we optimize the sigmoid function in order to get the best accuracy. But in a 2d plan, how does this reflect, how do we see the line ? When we optimize the sigmoid function, does the line change or not ?
Thanks in advance !
I'd like to see a video of polynomial regression from you :)
Amazing, this is such a clear and concise video. What do you use for your animations?
Manim CE, just Google it : )
Upload more videos for the all Algorithms in machine learning and deep learning
amazing video, Thank you very much
when are we getting the maximum likelihood video
😊😊😊
☯️🙏
Ｐｒⓞм𝕠𝕤𝐌
statquest is better explainer