DataRobot enables data science teams to become more efficient and productive. This book helps you address machine learning (ML) challenges with DataRobot’s enterprise artificial intelligence (AI) platform, enabling you to extract business value from data and quickly add value to your organization.
You’ll begin by learning how to use DataRobot’s features to perform data prep and cleansing tasks automatically. The book then 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. Next, 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 on an ongoing basis. Finally, you’ll work with examples on time series forecasting, NLP, image processing, MLOps, and more using advanced DataRobot capabilities.
By the end of this machine learning book, you’ll have learned to use DataRobot’s features to scale ML model building by avoiding repetitive tasks.
This book is for data scientists, data analysts, and data enthusiasts looking for a practical guide to building and deploying robust machine learning models using DataRobot. Experienced data scientists will also find this book helpful for rapidly exploring and building a broader range of models independently. The book assumes a basic understanding of machine learning.