Using AutoML solutions

Writing code from scratch to do machine learning requires specific knowledge that a generic analyst using Power BI often doesn't know. Therefore, we recommend the use of AutoML processes from here on out for analysts who do not have a data science background. Does this mean that anyone can create an accurate machine learning model without knowing the theory behind this science simply by using AutoML algorithms? Absolutely not! The following applies:

Important Note

An AutoML tool relieves the analyst of all those repetitive tasks typical of a machine learning process (hyperparameter tuning, model selection, and so on). Often, those tasks that require specific theoretical knowledge on the part of the analyst (for example, missing value imputation, dataset balancing strategies, feature selection, and feature engineering) are left out of the automated steps. Therefore, not applying the appropriate transformations that only an expert knows to the dataset...