Abhisake Jain·1d agoAny Curve Is a Straight Line If You Zoom In EnoughThis one trick is why neural networks can learn. And you already know it from looking at the Earth.A response icon1A response icon1
Sarbani·6d agoUnderstanding Gradient Descent in Deep Neural NetworksFrom measuring prediction errors to navigating the loss landscapeA response icon1A response icon1
Anandha L Ranganathan·Nov 1Regularization with Gradient descentPlease read here the gradient descent — introduction
Piyas De·Nov 1Gradient Descent: How AI Improves Step by StepAn AI model makes a prediction. The prediction is wrong. We calculate how wrong it is using a loss function. But then comes a more…A response icon1A response icon1
nachiket tanksale·Oct 30Day 4: Neural Network Backpropagation: What Is Actually Being Differentiated?Read Day 3 hereA response icon1A response icon1
Akshat Gupta·Oct 27ADAM Optimizer Vs Gradient DescentAdam also know as Adaptive momentum Estimation is an important Optimization Algorithm commonly used and most prefferable for Machine…
Anandha L Ranganathan·Oct 27Gradient descent -Part1How does a machine learn from its mistakes using gradient descent ?
Aditya Inamdar·Oct 27The Most Confident Model in the Room Has a Gradient of Exactly ZeroGoogle DeepMind found two numerical bugs in every framework’s softmax and cross-entropy. The fix is a few lines, and it takes bf16 test…A response icon1A response icon1
Akshat Gupta·Oct 26Gradient Exploding and Gradient VanishingGradient Descent is an iterative optimizaiton algorithm invovling continous update of model weights and parameters to achive most optimal…
Akshat Gupta·Oct 25Gradient Descent, Stochastic, Mini-Batch, Batch Gradient DescentIt is an iterative algorithm used to find most effecient weights and parameters/coeffeicients of modelA response icon1A response icon1
