How to easily provision an environment with GPU, H2O4GPU, TensorFlow, PyTorch, on Oracle Cloud.

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If you want to develop a Deep Learning model, or maybe use a Machine Learning framework like H2O, most certainly you will get great benefits from using an environment with a GPU.

But, it is not always easy the setup of such an environment. You need to find all the right versions for Nvidia drivers, TensorFlow, and all the other Open Source packages and tools and you risk to spend a lot of time, simply trying to figure out the correct and compatible versions.

In a previous article, I have described all the steps needed to set up a VM in Oracle Cloud, using Ubuntu 18 LTS. …

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Running on a multi-CPU VM


If you read an introductory book on Machine Learning (ML), the development of a model can seem always an easy, interesting and nice task. The reality, in a true business case, is quite different.

In the real world, the development of an effective model can be a difficult and rather long task. To achieve good predictive power, you need a lot of data (the more the better) and often many attempts with different algorithms and to define best values for the hyper-parameters of the model.

That is why often you need high computational power, to be able to iterate many executions in a reasonable time. …


If you want to develop a Deep Learning model and want a good likelihood to be successful, you need two things:

  • lots of data, for the training of the model
  • enough computational power, in the form of GPUs

A Deep Learning model commonly is based on a Deep (many layers) Neural Network. The algorithm commonly used for the training of the model is based on some form of the “back-propagation” algorithm and it requires many “tensor” operations. …


Luigi Saetta

Born in the wonderful city of Naples, but living in Rome. Always curious about new technologies and new things. I work in a big Cloud Company.

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