Ultimate Guide to APIs for Data Scientists

Ultimate Guide to APIs for Data Scientists

When you create a machine learning model in Python, and you want to fit it in a backend which is primarily based on Java or JavaScript, without web-services you would have had to rewrite one of codes in the other’s language. All web services are designed as APIs or Application programming interfaces. An API is an entry point into the system (way to access the code within the API).

When you create a machine learning model in Python, and you want to fit it in a backend which is primarily based on Java or JavaScript, without web-services you would have had to rewrite one of codes in the other’s language. All web services are designed as APIs or Application programming interfaces. An API is an entry point into the system (way to access the code within the API).

If you work in the Software Domain, you can’t not have heard about web services. Every company that relies on technology is moving towards a web service framework. They are easy to work on, they make the entire code modular, and since they integrate pieces of code written in different languages, it is also more efficient and easy to maintain.

What is a web service

A web service is a piece of software/code which offers a functionality to any other piece of code that wants to interact with it.

Why web services

As tech companies try to make their product or service better and quicker, they try to transition towards newer technologies and platforms. In this case, having a code that is tightly coupled to the technology or to the platform on which the older piece was built could be a tedious and sometimes a dangerous job.

In order to work around this problem, the code needs to be decoupled from the platform. This is precisely what web services aim to achieve. When you create a machine learning model in Python, and you want to fit it in a backend which is primarily based on Java or JavaScript, without web-services you would have had to rewrite one of codes in the other’s language. That would have cost you and your team a lot of rework and frustration, a.k.a Technical Debt. Tip: We always aim to reduce our technical debt.

As we aim to lower technical debt, we convert our code into web services and make them talk to each other. Now a Python based ML prediction model “service”, can speak to a MongoDB “service”, and return data to the user through a UI.

From Web Services to APIs

All web services are designed as APIs or Application programming interfaces. An API is an entry point into the system (way to access the code within the API).


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