Data Science in Python: Classification Modeling Course
Learn Python for Data Science & Supervised Machine Learning, and build classification models with fun, hands-on projects
This Data Science in Python: Classification Modeling Udemy Course Created by Maven Analytics and Chris Bruehl with 10 hours on-demand video, 3 articles, 2 downloadable resources and Certificate of completion. This is a hands-on, project-based course designed to help you master the foundations for classification modeling in Python.
What you’ll learn
Master the foundations of supervised Machine Learning & classification modeling in Python
Perform exploratory data analysis on model features and targets
Apply feature engineering techniques and split the data into training, test and validation sets
Build and interpret k-nearest neighbors and logistic regression models using scikit-learn
Evaluate model performance using tools like confusion matrices and metrics like accuracy, precision, recall, and F1
Learn techniques for modeling imbalanced data, including threshold tuning, sampling methods, and adjusting class weights
Build, tune, and evaluate decision tree models for classification, including advanced ensemble models like random forests and gradient boosted machines
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