From d3e7e4500da8240aa5fbbc6026f8e357d81cfe43 Mon Sep 17 00:00:00 2001 From: nprimo Date: Tue, 12 Mar 2024 11:49:22 +0000 Subject: [PATCH] chore: run prettier --- subjects/ai/training/README.md | 2 +- subjects/ai/training/audit/README.md | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/subjects/ai/training/README.md b/subjects/ai/training/README.md index db390147b..332311629 100644 --- a/subjects/ai/training/README.md +++ b/subjects/ai/training/README.md @@ -179,7 +179,7 @@ classifier.fit(X_train_scaled, y_train) ![alt text][logo_ex4] -[logo_ex4]: ./w2_day4_ex4_q3.png 'ROC AUC ' +[logo_ex4]: ./w2_day4_ex4_q3.png "ROC AUC " - https://scikit-learn.org/stable/modules/generated/sklearn.metrics.plot_roc_curve.html diff --git a/subjects/ai/training/audit/README.md b/subjects/ai/training/audit/README.md index 75fe7a9a3..e654feac1 100644 --- a/subjects/ai/training/audit/README.md +++ b/subjects/ai/training/audit/README.md @@ -115,7 +115,7 @@ array([[37, 2], ![alt text][logo_ex4] -[logo_ex4]: ../w2_day4_ex4_q3.png 'ROC AUC ' +[logo_ex4]: ../w2_day4_ex4_q3.png "ROC AUC " Having a 99% ROC AUC is not usual. The data set we used is easy to classify. On real data sets, always check if there's any leakage while having such a high ROC AUC score.