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Loss functions are the backbone of training deep learning models. In this video, we explore what loss functions are, why they’re important, and how they guide model optimization. Learn about popular loss functions like Mean Squared Error (MSE), Cross-Entropy Loss, and more, with examples for both regression and classification tasks. Whether you’re a beginner or looking to deepen your understanding, this video will help you grasp the core concepts of loss functions in AI.
🔍 Topics Covered:
1.Types of loss functions (MSE, Cross-Entropy, etc.)
2.Choosing the right loss function for your task
3.Visualizing loss and its role in optimization
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#LossFunctions: #CrossEntropyLoss #BinaryCrossEntropy #CategoricalCrossEntropy #MeanSquaredError #HuberLoss #SmoothL1Loss #HingeLoss #KLDivLoss #TripletMarginLoss #FocalLoss #CustomLossFunction
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