Productization

As we saw in How to productize your machine learning model using Scikit-learn [1/2], it is crucial that production-ready code is versionable, testable, manageable, and integrable. After understanding these concepts and why it is important not to use Jupyter notebooks to productize your model pipeline, let’s look at a practical example of transforming prototype code…

“IT leaders responsible for AI are discovering ‘AI pilot paradox’, where launching pilots is deceptively easy but deploying them into production is notoriously challenging”. Chirag Dekate, Senior Director Analyst, Gartner VentureBeat reported that 87% of data science projects never reach production [1], and Gartner predicted in 2018 that by 2022, 85% of AI projects would yield incorrect…