Machine Learning
1,608 learners
Classification Algorithms and Metrics
Go beneath the surface of classification algorithms and metrics, implementing them from scratch for deeper understanding. Bypass commonly-used libraries such as scikit-learn to construct Logistic Regression, k-Nearest Neighbors, Naive Bayes Classifier, and Decision Trees from ground up. This course includes creating the AUCROC metric for Logistic Regression, among others.
Python
6 lessons
27 practices
5 hours
Badge for Machine Learning Model Development,
Machine Learning Model Development
Course details
Understanding the Confusion Matrix, Precision, and Recall in Classification Metrics
Calculating True Negatives and False Positives in Medical Diagnostics
Precision and Recall in Medical Diagnostics
Precision Calculation in Medical Diagnostics
Medical Test Recall Calculation Correction
Calculating Precision and Recall in Medical Diagnostics
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