Preface

DataRobot enables data science teams to become more efficient and productive. This book helps you address machine learning (ML) challenges with DataRobot's enterprise platform, enabling you to extract business value from data and rapidly generate commercial impact for your organization.

You'll begin by learning how to use DataRobot's features to perform data prep and cleansing tasks automatically. The book covers best practices for building and deploying ML models, along with challenges faced while scaling them to handle complex business problems. Moving on, you'll perform exploratory data analysis (EDA) tasks to prepare your data to build ML models and ways to interpret results. You'll also discover how to analyze the model's predictions and turn them into actionable insights for business users. After that, you'll create model documentation for internal as well as compliance purposes and learn how the model gets deployed as an API. In addition, you'll find out how to operationalize and monitor the model's performance. Finally, you'll work with examples of time series forecasting, NLP, image processing, MLOps, and more using advanced DataRobot capabilities.

By the end of this book, you'll have learned how to use some of the AutoML and MLOps features DataRobot offers to scale ML model building by avoiding repetitive tasks and common errors.