Machine Learning lectures

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PCA from Geometric Intuition to Eigenvectors 22 views

The Transformer: From Recurrence Failure to Attention 26 views

Support Vector Machines: Maximum-Margin Separation and the Kernel Trick 2 views

Backpropagation by Hand: From Computational Graphs to Matrix Gradients 4 views

Overfitting Made Visible: Bias, Variance, and the Role of Data 6 views

Diffusion Models: From Noise to Images 8 views

Gradient Descent: How the Learning Rate Shapes the Journey 8 views

Inside Kimi K3: Architecture of an Open Frontier Model 12 views

K-Means, Its Failure Modes, and Gaussian Mixture Models 3 views

From One Decision Tree to a Random Forest 5 views