Experiment your own Machine Learning (ML) models, by choosing TensorFlow

Steadily, one can observe that, companies are starting to experiment with their own ML models, and a lot of them are choosing TensorFlow.

For those who are unfamiliar, TensorFlow is open source, you can run it locally to quickly create prototypes and deploy fail-fast experiments that help you get your proof-of-concept working at a small scale.

You can take TensorFlow, your data, and the same code and push it up into Google Cloud to take advantage of multiple CPUs, GPUs or soon even some TPUs.

Google have published a pair of solution tutorials to show you how you can create and run a distributed TensorFlow cluster on Google Compute Engine and run the same code to train the same model on Google Cloud Machine Learning Engine.