Model pipelines explain how an automated machine learning platform analyzes data to uncover patterns and trends – so that they can then provide insights and make predictions from that data.
The model pipelines include feature engineering, which involves cleaning up the training dataset so that it only consists of the information needed to support the target variable. It provides other preprocessing stems as well, making the machine learning algorithms more comfortable to understand.
Avoiding the black box issue is essential – this is when end-users have no insights into how the machine learning model arrived at the specific output. With tools like model pipelines, the interpretability of machine learning algorithms is improved, allowing businesses to rely on the model’s predictions to make data-driven decisions.
Model pipelines are vital because they allow data scientists to automate testing a wide variety of modeling approaches.
There is not always an obvious answer when trying to determine the best type of machine learning algorithm to solve your unique business problem. In other words, there is no one right or consistent way to solve all problems, and no one algorithm can be perfect at learning everything.
Using model pipelines cuts down the time it would otherwise take to manually test out several different types of models, which results in better decisions and selection of the most accurate model. This also helps to minimize the possibility that data scientists rely too heavily on one type of algorithm.
It doesn’t matter if you only have BI analysts, IT leaders, or executives wanting to leverage model pipelines or if you have a team of in-house data scientists looking to be more impactful with their analytic output. Any organization looking to start or advance their AI journey can benefit from model pipelines.
At LogicPlum, our sophisticated automated machine learning platform comes equipped with a wide variety of model pipelines that have been thoroughly tested and developed with your needs in mind.
Our expert data scientists will help you walk through the purpose of your machine learning model and explain the diverse modeling approaches available to solve it. We are always continuing to test and grow our machine learning algorithm library, so you can be confident you are working with the most up to date technology.
LogicPlum’s model pipelines will provide a step-by-step guide to the model, increase interpretability, and allow you to completely understand what is going on in the background.