GCP is very focused on the machine learning algorithm and provides a huge variety of technologies to build an analytical model. These include BigQuery, Dataflow, Data Studio, Prebuilt-Model, and Engine ML. GCP has also developed its own Tensor Processing Unit (TPU) processor to speed up the adoption of ML both on the cloud and on the edge (https://cloud.google.com/edge-tpu/). GCP supports ML through the Google Cloud ML service (https://cloud.google.com/ml-engine/).
Understanding the advanced analytics capabilities of GCP
ML Engine
The process to develop a model using the ML Engine is quite similar to that we have seen in the Working with the Azure ML service and Implementing analytics on AWS SageMaker sections:
- Develop the...