With GCP, you have multiple options when it comes to leveraging ML. Which one you choose largely depends on your use case and how knowledgeable you are on the topic. The following options are available:
- TensorFlow (for data scientist): This is an option for those who want to work with ML from scratch. It is a software library that's developed and open-sourced by Google. There are more libraries on the market, but this one is the most popular and is used by other cloud providers for their managed ML services.
- ML Engine (for data scientist): This is an option for those who want to train their own models, but who use Google for training and predictions. It is a managed TensorFlow service that offloads all infrastructure and software bits from users.
- Pretrained ML models (for developer): This is an option for those who want to leverage ML without having any knowledge...
