This workshop is a good fit for you if you’re a student or researcher relatively new to TensorFlow or JAX (or you're curious about what's new!), and you’d like to learn more about Google’s open-source tools.
The workshop will be divided into two sections. Each section will include a presentation about the library followed by examples you can try to illustrate key points.
We'll start with TensorFlow, and cover new features in TensorFlow 2.10 and 2.11. We'll discuss plans for future iterations of the library, and then we'll explore your options as a researcher. You'll learn about TensorFlow's core APIs from the ground up, and then explore Keras with a progressive disclosure of complexity, from simple sequential APIs, to model subclassing and custom training loops for full control.
Next, you'll learn how to get started with JAX. JAX is a high-performance library for machine learning research, with a familiar NumPy API. In this section of the workshop, you’ll learn about JAX as accelerated NumPy, and explore features like Just in Time Compilation, Automatic Vectorization, and Parallelism.
The presenters will be available to chat with you 1:1 after to learn more about your work and how Google’s tools can help.
Please bring a laptop. There is nothing to install in advance. Thank you!