Results for: tpu

​JAX is a Python library designed for high-performance numerical computing and machine learning research. It offers a NumPy-like API, facilitating seamless adoption for those familiar with NumPy. Key features of JAX include automatic differentiation, just-in-time compilation, vectorization, and parallelization, all optimized for execution on CPUs, GPUs, and TPUs. These capabilities enable efficient computation for complex mathematical functions and large-scale machine-learning models. JAX also...

... ideas than your competition, faster. And this is how you win. Built on top of TensorFlow 2.0, Keras is an industry-strength framework that can scale to large clusters of GPUs or an entire TPU pod. It's not only possible; it's easy. Take advantage of the full deployment capabilities of the TensorFlow platform. You can export Keras models to JavaScript to run directly in the browser, to TF Lite to run on iOS, Android, and embedded devices. It's also easy to serve Keras models as via a web API.

Run advanced apps on a secured and managed Kubernetes service. GKE is an enterprise-grade platform for containerized applications, including stateful and stateless, AI and ML, Linux and Windows, complex and simple web apps, API, and backend services. Leverage industry-first features like four-way auto-scaling and no-stress management. Optimize GPU and TPU provisioning, use integrated developer tools, and get multi-cluster support from SREs. Start quickly with single-click clusters. Leverage...