In 2017, Google announced a Tensor Processing Unit (#TPU) — a custom application-specific integrated circuit (ASIC) built specifically for #machinelearning. A year later, TPUs were moved to the cloud and made open for commercial use.

Following the line of CPUs and GPUs, Tensor Processing Units (TPUs) are Google’s custom-developed application-specific integrated circuits (ASICs) that are supposed to accelerate machine learning workloads. They are designed specifically for Google’s #TensorFlow framework, a symbolic math library that is used for #neuralnetworks.

https://medium.com/sciforce/understanding-tensor-processing-units-10ff41f50e78

Keras / TPU integration in Tensorflow 2.1 (unreleased)
Google Cloud Platform : https://github.com/GoogleCloudPlatform/training-data-analyst/blob/master/courses/fast-and-lean-data-science/README-TF2.1.md
#Keras #TPU #Tensorflow https://t.me/ArtificialIntelligenceArticles

Keras / TPU integration in Tensorflow 2.1 (unreleased)

Google Cloud Platform : https://github.com/GoogleCloudPlatform/training-data-analyst/blob/master/courses/fast-and-lean-data-science/README-TF2.1.md

#Keras #TPU #Tensorflow