Training loss: Revision history

17 March 2023

• curprev 21:2021:20, 17 March 2023‎ Alpha5 talk contribs‎ m 3,678 bytes +25‎ Text replacement - "Category:Machine learning terms" to "Category:Machine learning terms Category:not updated"

26 February 2023

• curprev 10:0710:07, 26 February 2023‎ Alpha5 talk contribs‎ 3,653 bytes +8‎ →‎Types of Loss Functions
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25 February 2023

• curprev 23:3123:31, 25 February 2023‎ Alpha5 talk contribs‎ 3,783 bytes +3,783‎ Created page with "{{see also|Machine learning terms}} ==Introduction== Training loss is an important metric in machine learning that measures the discrepancy between predicted output and actual output. It helps evaluate a model's performance during training, with the aim being to minimize this loss so that it can generalize well on unseen data. ==Types of Loss Functions== Machine learning employs a variety of loss functions, depending on the problem being solved and the model being emplo..."