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Virtual Machines for Data Science

With the explosion of business data—ranging from customer data to the Internet of Things—data scientists need the flexibility to explore and build models quickly. But purchasing new hardware to meet temporary or peak demand can involve significant capital expense as well as a considerable amount of time.

Oracle Cloud Infrastructure Virtual Machines (VMs) for Data Science are preconfigured environments that enable you to build models and deliver business value faster. Built on Oracle Cloud Infrastructure, these VMs offer exceptional performance, security, and control. You can expand your compute resources as needed using compute autoscaling and keep costs under control by stopping compute instances when they are not needed.

Compute options suitable for this VM image include a virtual machine with an NVIDIA GPU that can be up and running in under 15 minutes with preinstalled common IDEs, notebooks, and frameworks. Oracle Cloud Infrastructure VMs for Data Science include basic sample data and code for you to test and explore.

Major wireless carrier achieves faster performance with AI solution built on Oracle Cloud Infrastructure

A large mobile network operator delivers an AI-powered virtual voice assistant in multiple languages to millions of users. The environment uses a cluster with 2 nodes of 8 GPUs each, connected as a cluster with 16 GPUs and 768GB of memory in each node, significantly reducing the training time of the model.

The solution uses 100 million trainable parameters optimized in each iteration. Results include a speech-to-text performance increase of 2.4x and text-to-speech handled 30 to 50 percent faster, along with faster training of models.

Use Cases

Oracle’s preconfigured environment for deep learning is useful in many industries across a wide range of applications.

  • Natural language processing

  • Image recognition and classification

  • Fraud detection for financial services

  • Recommendation engines for online retailers

  • Risk management