Machine Learning with Python: Case Studies
Build practical machine learning skills with Python through projects based on real-world datasets. You’ll begin by setting up your environment and applying linear, polynomial, robust, and logistic regression to model relationships, optimize predictions, and solve classification problems. As you progress, you’ll implement k-means clustering, calculate centroids, and visualize data distributions. You’ll also prepare sequential datasets and interpret time series forecasts using airline passenger and Bitcoin price data. Classification projects introduce logistic regression, decision trees, KNN, L
Skills you'll learn
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