Machine Learning
JAX in Action: Neural Networks from Scratch
This course guides you through building a simple Multi-Layer Perceptron (MLP) from scratch using only JAX and its NumPy API. You'll tackle the classic XOR problem, learning how to manage model parameters as PyTrees, implement the forward pass, define a loss function, compute gradients, and write a manual training loop with a basic optimizer step.
JAX
Python
4 lessons
15 practices
2 hours
Course details
Perfecting XOR Data for Neural Networks
Defining Neural Network Layer Sizes
Mastering Neural Network Weight Initialization
Building MLP Parameter Initialization
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