Discover the advantages of Machine Learning with Google Cloud Platform

Hyper-accessible machine learning

Google Cloud AI Platform is designed to make it easy for data scientists and data engineers to streamline ML workflows, and access groundbreaking AI developed by Google. We use it a lot with AutoML (Google’s point-and-click ML engine), but in addition, it supports training, prediction, and version management of advanced models built using Tensorflow, and SKLearn.

Use AI Platform to train your machine learning models at scale, host your trained model in the cloud, and use your model to make predictions about new data.

MLOps practice for communication and collaboration

ML can be a game-changer for a business, but without some form of systemization, it can devolve into a science experiment. The real challenge isn't building an ML model, the challenge is building an integrated ML system and continuously operate it in production.

MLOps is a practice for collaboration and communication between data scientists and operations professionals to help manage the production ML lifecycle. It is an ML engineering culture and practice that aims at unifying ML system development (Dev) and ML system operation (Ops).

Machine Learning

Exploit your unstructured data. Make smarter predictions with Artificial Intelligence and Machine Learning.

What is Machine learning?

Introduction to Google AI Platform

Hyper-accessible machine learning

Where does AI Platform fit into the ML workflow

MLOps practice for communication and collaboration

Would you like to know more about machine learning? Contact us!

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