- Видео 10
- Просмотров 11 760
AIRCO_Lab
Сингапур
Добавлен 20 окт 2022
Sharing that goes beyond academia.
We are a group of young lecturers and professors from the budding AI Research and Computational Optimization (AIRCO) lab.
We are a group of young lecturers and professors from the budding AI Research and Computational Optimization (AIRCO) lab.
Видео
Remove Comment Timestamps for Microsoft Word
Просмотров 188 месяцев назад
Remove Comment Timestamps for Microsoft Word
Anaconda Jupyter Installation & Google Colab
Просмотров 49511 месяцев назад
Install Anaconda Jupyter Notebook/Lab; and how to use Google Colab (3:14)
SVM - Kernel Functions for Non-Separable Case with Numerical Examples
Просмотров 341Год назад
Watch Part 1 first: ruclips.net/video/6FQ-t5SOEUk/видео.html Numerical Examples; Support Vector Machines (SVM); Kernel; Polynomial Kernel; Radial Basis Function (RBF) Kernel; Linearly Non-Separable Problem;
三菱空调清洗和去除异味 (Mitsubishi Aircon General Cleaning and Odor Removal)
Просмотров 6 тыс.2 года назад
三菱空调清洗和去除异味 (Mitsubishi Aircon General Cleaning and Odor Removal)
Support Vector Machines (SVM) Numerical Example
Просмотров 3,2 тыс.2 года назад
Numerical Example; Support Vector Machines (SVM); Linear Separable Problem;
Thank You
Hey great video!! Can u please tell me how to fix the version error
thank you for the explanation, you really helped me a lot
btw, if it doesn't bother you, may i ask what the source of this video, like a book or anything that you can recommend to understand math behind machine learning better, thank you!
Treasure!
It says keras/src not found. Is there a solution for that ?
seems you didn't install keras on Pythonanywhere. Go to the bash and run pip install keras.
@@airco_lab when I do, it gives storage error since it is limited. Anyways I sorted it out. Apparently it have keras installed for some specific versions of Python such as 10.2.
Thank you for helping me ❤❤
my pleasure, glad it helps :)
Thank you for helping me ❤❤
Very good explanation. Thank you
You're most welcome.
I was dying to understand SVM until I saw your video, Thank You !
Thank you so much ! amazing video could you also explain how to solve it using kernel trick
Thank you for your kind words. Indeed, I have recently uploaded a new video that delves into the use of Polynomial and RBF Kernels in SVM for addressing linearly non-separable cases. You're welcome to view it at this link: ruclips.net/video/DjjE-ubDOos/видео.html