Classical Machine Learning: From Regression to Ensembles

<p>Follow Dana Whitfield, the first data scientist hired at Cascadia Fiber, a fictional regional internet provider losing subscribers to churn faster than sales can replace them. Working with VP of Customer Success Priya Malhotra, Dana builds an end-to-end classical machine learning toolkit in scikit-learn &mdash; linear and logistic regression, decision trees, random forest and gradient boosting ensembles, a kernel SVM, and k-means clustering &mdash; while learning the train/test splitting, cross-validation, overfitting, and evaluation-metric discipline that makes each model trustworthy enough to act on.</p>

Tools: scikit-learn, Linear & Logistic Regression, Decision Trees & Ensembles, SVM, Clustering, Model Evaluation