ML Katas

JAX's `jit` function will compile your Python code, which can lead to significant speedups. This is because JAX can fuse operations together, removing the overhead of Python's interpreter. In this...

When you `jit` a function, JAX traces it to determine its computational graph. This graph is then compiled by XLA for efficient execution. However, this tracing mechanism has some implications....

Your task is to implement a simple linear regression model from scratch using JAX. You'll need to define the model, a loss function (like Mean Squared Error), and a gradient descent update rule....

In JAX, standard Python `print` statements don't always work as expected within `jit`-compiled functions because they execute at trace time. [11] The solution is to use `jax.debug.print`. [11, 23]...