Shypd.aiThe largest open index of AI toolsstat479-machine-learning-fs18 provides course materials for STAT 479: Machine Learning at the University of Wisconsin-Madison. It includes lecture content from Fall 2018, covering topics like supervised learning and KNN.
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STAT479-machine-learning-fs18 offers comprehensive course materials for the STAT 479: Machine Learning class taught by Sebastian Raschka at the University of Wisconsin-Madison in Fall 2018. The repository contains lecture content, homework assignments, and other resources. Key topics covered include an introduction to supervised learning with K-Nearest Neighbors, computational foundations using Python, NumPy, SciPy, Matplotlib, and Scikit-Learn, and tree-based methods like Decision Trees and Ensemble Methods. It also delves into various aspects of model evaluation, including overfitting, underfitting, uncertainty estimates, cross-validation, algorithm selection, and performance metrics. Additionally, the course material addresses dimensionality reduction through feature selection and extraction.
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