In this video, you will learn all about the details of support vector machines. You'll learn about tuning hyperparameters for these models and using kernels to fit non-linear decision boundaries.
Datasets
https://drive.google.com/drive/folder...
Links
Python: https://www.python.org/downloads/ PyCharm: https://www.jetbrains.com/pycharm/dow... scikit-learn: https://pypi.org/project/scikit-learn/ pandas: https://pypi.org/project/pandas/ numpy: https://pypi.org/project/numpy/ matplotlib: https://pypi.org/project/matplotlib/
Chapters
0:00 Chapter Introduction
00:05 Support vectors
02:46 kernel SVMs
05:35 Comparing logistic regression and SVM