37:55
ML TA01- Python Basics 1
54:17
ML TA02 - Python Basics 2
29:50
ML07 3 - Support Vector Machine (Mathematical foundations, Dual problem, Kernel Trick)
35:41
ML07 2 - Support Vector Machine (Hard margin vs Soft margin)
23:55
ML07 1 - Support Vector Machine (SVM) - Python implementation
11:01
ML04 2 - Regression algorithms in Colab (Liver dataset)
31:09
ML06 2 - Regularized models, Logistic Regression, Softmax
01:02:39
ML06 1 - Training Models (Least square estimation, Gradient-based approaches)
01:09:56
ML05 -MNIST Dataset classification
57:49
ML04 - Data preparation, Implementation of regression models with Scikitlearn
01:17:47
ML03- A practical Machine Learning project with Scikitlearn
49:54
ML02 - Types of learning algorithms, Curve fitting and regression
01:00:54
ML01 - The machine learning landscape
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