GitHub - NILAY2233/Machine_Learning--Learning-Gradient-Descent-optimization-technique: Gradient Descent is a technique used to fine-tune machine learning algorithms with differentiable loss functions. It's an open-ended mathematical expression, tirelessly calculating the first-order derivative of a loss function and making precise parameter adjustments.

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Gradient Descent is a technique used to fine-tune machine learning algorithms with differentiable loss functions. It's an open-ended mathematical expression, tirelessly calculating the first-order derivative of a loss function and making precise parameter adjustments.

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Name		Name	Last commit message	Last commit date
Latest commit History 2 Commits
Batch_Gradient_Descent - Cost_Function with increasing epoch.mp4		Batch_Gradient_Descent - Cost_Function with increasing epoch.mp4
Coding from scratch - Mini-Batch Gradient Descent Algorithm.ipynb		Coding from scratch - Mini-Batch Gradient Descent Algorithm.ipynb
Coding from scratch -- Batch Gradient Descent Algorithm.ipynb		Coding from scratch -- Batch Gradient Descent Algorithm.ipynb
Coding from scratch -- Stochastic Gradient Descent Algorithm.ipynb		Coding from scratch -- Stochastic Gradient Descent Algorithm.ipynb
Mini-batch_Gradient_Descent - Cost_Function with increasing parameter updates.mp4		Mini-batch_Gradient_Descent - Cost_Function with increasing parameter updates.mp4
Stochastic_Gradient_Descent - Cost_Function with increasing parameter updates.mp4		Stochastic_Gradient_Descent - Cost_Function with increasing parameter updates.mp4