Welcome to the first article in this series about doing Machine Learning stuff on the Google Cloud Platform!

We will take a look at the AI Platform. It is a subset of tools strictly related to Machine Learning, among which:

• AI Platform Training, for training/tuning models on the cloud
• AI Platform Prediction, to host trained models on the cloud
• AI Pipelines, to create a step-by-step process using Kubernetes and Docker Images

and many others.

DISCLAIMER: I am not affiliated with Google in any way, I simply decided to

write these articles to share the knowledge I acquired using these tools in my

daily job.

For this first article, I’ll focus on AI Platform Training, a product to run

training jobs on the Cloud with custom code and customizable machines. I think the main advantages of using the AI Platform to train your models are:

• you can use more powerful resources (like multiple cores or a GPU) without a lot of hassle to instantiate them
• you can share the code with your team and reproduce the same results using a common Cloud infrastructure

#data-science #google #cloud-computing #google-ml-tutorials #machine-learning