If you’re wondering which of the growing suite of programming language libraries and tools are a good choice for implementing machine-learning models then help is at hand.

More than 1,300 people mainly working in the tech, finance and healthcare revealed which machine-learning technologies they use at their firms, in a new O’Reilly survey.

The list is a mix of software frameworks and libraries for data science favorite Python, big data platforms, and cloud-based services that handle each stage of the machine-learning pipeline.

Most firms are still at the evaluation stage when it comes to using machine learning, or AI as the report refers to it, and the most common tools being implemented were those for ‘model visualization’ and ‘automated model search and hyperparameter tuning’.

Unsurprisingly, the most common form of ML being used was supervised learning, where a machine-learning model is trained using large amounts of labelled data. For instance, a computer-vision model tasked with spotting people in video might be trained on images annotated to indicate whether they contain a person.