These lecture slides are from an introductory course on machine learning which I teach at Tilburg University. It does not presuppose any background in math or computer science, but the practical parts do assume basic knowledge of Python.
- Introduction. What is machine learning. Slides
- Representations. K-Nearest-neighbors. Slides
- Decision Trees. Slides
- Perceptron. Slides
- Gradient descent. Slides
- Logistic regression. Slides
- Clustering and unsupervised learning (guest lecture by Afra Alishahi). Slides
- Neural networks. Slides
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k-Nearest Neighbors
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Perceptron
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