Google cloud for ML engineers

Data Science, AI and ML
#1

Get started with Google cloud and explore the platform.
First reason to do the same is that, Google Cloud public datasets provide a playground for those new to big data and data analysis and offers a powerful data repository of more than 100 public datasets from different industry verticals, allowing you to join these datasets with your own, to produce new insights. These will be good to showcase on your resume.

Additionally, GCP offers products such as AutoML, visionAPI and BigQueryML.

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#2

Roughly visualizing, underneath the GCP products for ML, there is a layer that contains 3 components, Compute power, Storage and Networking. This layer is further wrapped by google’s security.

For more information on how to get started using GCP follow this simple blog. Steps summarized are below:

  1. Register
  2. Create new project and instance
  3. Setup external IP and firewal
  4. Connect to your instance
  5. Setup your working environment
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