In the last few years, Artificial Intelligence and Machine Learning have seen an unprecedented rise in popularity across industries and areas of scientific research. Businesses are looking for ways to integrate these new technologies into their operations. However, the shortage of qualified data scientist and machine learning experts has been one of the challenges which thwart the adoption of AI. But a growing number of tools are bringing these capabilities into the hands of developers, citizen data scientists, domain experts and business users. In this blog, we will delve into Automated Machine Learning (AutoML) for Data Flows – a new capability in Power BI which enables business users to experience machine learning models without having to learn how to program or extensive knowledge of mathematics and statistics. AutoML for dataflows allows users to create Machine Learning models with few simple clicks and generates model summary reports.

Automated Machine Learning (Auto ML) in Power BI is a powerful feature that is designed to automate the process of machine learning and allows users to successfully transform tasks like data imputation, feature engineering, model selection, training, testing and visualizing their results. Microsoft has introduced this incredibly smart feature to enable people with relatively little or no knowledge of Machine Learning. Auto ML is not only time-efficient, it also gets quality results in a reasonable amount of time for its users. It is important to understand that this feature, regardless of how innovative and efficient it is, does not replace all the machine learning techniques out there. In fact, there are many custom applications that cannot be applied to this feature.

Earlier this year, we introduced Automated Machine Learning (AutoML) in Power BI as Public Preview. Now, we're happy to announce that AutoML in Power BI is generally available in all public cloud regions where Power BI Premium and Embedded is available. Using AutoML in Power BI, business analysts without a strong background in machine learning can build ML models to solve business problems that once required data scientists. Most of the data science behind the creation of the ML models is automated by Power BI, while giving visibility into the process used to create your ML model to provide you with full insight. Since AutoML targets analysts who may not have prior experience building ML models, we have made a significant investment in adding automatic guardrails such as class balancing, training-test data split, cross-validation, missing value imputation, and high cardinality feature detection to ensure that the model produced has good quality.