Machine Learning lectures

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PCA from Geometric Intuition to Eigenvectors 37 views

The Transformer: From Recurrence Failure to Attention 42 views

Support Vector Machines: Maximum-Margin Separation and the Kernel Trick 5 views

Backpropagation by Hand: From Computational Graphs to Matrix Gradients 9 views

Overfitting Made Visible: Bias, Variance, and the Role of Data 11 views

Diffusion Models: From Noise to Images 13 views

Gradient Descent: How the Learning Rate Shapes the Journey 13 views

Inside Kimi K3: Architecture of an Open Frontier Model 14 views

K-Means, Its Failure Modes, and Gaussian Mixture Models 6 views

From One Decision Tree to a Random Forest 8 views