Analyzing Logistic Regression Performance with ROC Curves [Part 17] | Machine Learning for Beginners

Lessons17 lessons

• ✓1Introduction to Machine Learning for Beginners [Part 1] | Machine Learning for Beginners
• ✓2The history of Machine Learning [Part 2] | Machine Learning for Beginners
• ✓3Techniques for Machine Learning [Part 3] | Machine Learning for Beginners
• ✓4Setup your tools ready to build Machine Learning models [Part 4] | Machine Learning for Beginners
• ✓5Introduction to Regression models for Machine Learning [Part 5] | Machine Learning for Beginners
• ✓6Set up Jupyter Notebooks to start building regression models [Pt 6] | Machine Learning for Beginners
• ✓7Your First Linear Regression Project in Python [Part 7] | Machine Learning for Beginners
• ✓8How to Analyze and Clean a Dataset [Part 8] | Machine Learning for Beginners
• ✓9How to Visualize Data with Matplotlib [Part 9] | Machine Learning for Beginners
• ✓10Understanding Linear Regression [Part 10] | Machine Learning for Beginners
• ✓11Looking for Correlation: The Key to Linear Regression [Part 11] | Machine Learning for Beginners
• ✓12Linear and Polynomial Regression using Scikit-learn [Part 12] | Machine Learning for Beginners
• ✓13Categorical Feature Predictions with Linear Regression [Part 13] | Machine Learning for Beginners
• ✓14Understanding Logistic Regression for Machine Learning Classification [Part 14] | ML for Beginners
• ✓15Data Analysis and Preparation for Logistic Regression [Part 15] | Machine Learning for Beginners
• ✓16Logistic Regression for classification of data [Part 16] | Machine Learning for Beginners
• ✓17Analyzing Logistic Regression Performance with ROC Curves [Part 17] | Machine Learning for Beginners

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