Could you explain the binary loss function in the code in relation to the one explained in the video?

loss_reg_1 = -1 * np.sum(y_true * np.log(y_pred_1)) + (-1 * np.sum((1 - y_true) * np.log(1 - y_pred_1)))

video link:
https://www.coursera.org/learn/ai-for-medical-diagnosis/lecture/qSNmX/impact-of-class-imbalance-on-loss-calculation

I think its better you should read this article or similar can be found in the web that explains it in detailed manner.

Binary Cross Entropy/Log Loss for Binary Classification.

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