What is your most favorite IDE? A developer can mention various of IDE’s. How about data scientist?
Normally, the Developers develop the code and data scientists train develop and train the model. Tools such as VSCode come in handy as easy to install and use. Many have many preferences so the chances are that it can be a choice of the developer or the development team. Usually the trained model is handed over to the app developer for integrating it and build the final application. There are times where the mismatches in compatibility can cost both the app developer and the model developer. The resulting friction between app developers and data scientists to identify and fix the root cause can be a slow, frustrating, and expensive process
We often here organizations including managers continuously talking about Artificial Intelligence. People like to find solutions that are integrated with AI. So as the developers have a development lifecycle, the data scientists follow a data science lifecycle.
The lifecycle includes processes such as,
Data Ingestion --> Data Preparation --> Model Development --> Model Deployment
There can be many iterations of this lifecycle as there can be requirements for changing the data labels, removing anomalies, changes upon user feedback and timely decision changes and many more.