This project is a study of effects that different activation functions have on how the gradients change in time. A simple 7-layer fully connected neural networks was used on a simulated dataset with 3 ...

The article aimed to demonstrate how we compile a neural network by defining loss function and optimizers. In this article, we also discussed what gradient descent is and how it is used. At last, we ...

For multivariable functions, partial derivative measures the rate of change with respect to each of the independent variables. It is also referred to as the gradient of the function. The gradient of a ...

Dive deep into Nesterov Accelerated Gradient (NAG) and learn how to implement it from scratch in Python. Perfect for improving optimization techniques in machine learning! 💡🔧 # ...