Why are APIs Important for Data Science?
In this video @Tiff In Tech and I give you some insight into what APIs are and how they are useful in the field of data science.
I think that APIs are one of the most underrated tools that data scientists use or implement.
Why are APIs important for data scientists?
1) Great way to access new data or build consistency around a data pipeline
2) One of the most efficient ways to share our models or findings with software engineers or other data scientists
3) Leveraging pre built models so we don't have to do rework
How to use API's - All apis are a little bit different, but most of the times you send a request to the API endpoint. With that request you can either receive back data or a service, or request that the api makes a change to the system that it is attached to.
How to create APIs - APIs consist mostly of a web server forwarding on a process to another application. You can build an api by creating a web server in flask, fast api, or other libraries and hosting it on the cloud.