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Scaling Jupyter notebooks with Kubernetes and Tensorflow
One of the most common hurdles with developing AI and deep learning models is to design data pipelines that can operate at scale and in real-time. Data scientists and engineers are often expected to learn, develop and maintain the infrastructure for their experiments, but the process takes time away from focussing on training and developing the models. But what if you could outsource all of the non-data science to someone else while still retaining control? In this article, you will explore how you can leverage Kubernetes, Tensorflow and Kubeflow to scale your models without having to worry about scaling the infrastructure.
tensorflow  k8s 
3 days ago by lenciel
Scaling Jupyter notebooks with Kubernetes and Tensorflow ♦︎ learnk8s
One of the most common hurdles with developing AI and deep learning models is to design data pipelines that can operate at scale and in real-time. Data scientists and engineers are often expected to learn, develop and maintain the infrastructure for their experiments, but the process takes time away from focussing on training and developing the models. But what if you could outsource all of the non-data science to someone else while still retaining control? In this article, you will explore how you can leverage Kubernetes, Tensorflow and Kubeflow to scale your models without having to worry about scaling the infrastructure.
tensorflow  jupyter  kubernetes  data.science 
4 days ago by tonious

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