Book Image

Agile Machine Learning with DataRobot

By : Bipin Chadha, Sylvester Juwe
Book Image

Agile Machine Learning with DataRobot

By: Bipin Chadha, Sylvester Juwe

Overview of this book

DataRobot enables data science teams to become more efficient and productive. This book helps you to address machine learning (ML) challenges with DataRobot's enterprise platform, enabling you to extract business value from data and rapidly create 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 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. 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 book, you'll have learned to use DataRobot's AutoML and MLOps features to scale ML model building by avoiding repetitive tasks and common errors.
Table of Contents (19 chapters)
1
Section 1: Foundations
5
Section 2: Full ML Life Cycle with DataRobot: Concept to Value
11
Section 3: Advanced Topics

Building models and the model leaderboard

Once we are done making any changes to the configuration settings, we can scroll up and click the Start button. DataRobot will now start automatically building the models, as illustrated in the following screenshot:

Figure 6.7 – Automated building of models

You can see which models DataRobot is building and how much training data is being used. You will notice that DataRobot will first build quick models with smaller datasets, learn which one performs better, and then selectively build models with more data. In the present case, you might not see this because there is very little data to begin with. Once DataRobot is done building the models, it will show the model leaderboard, as illustrated in the following screenshot:

Figure 6.8 – Model leaderboard

In the preceding screenshot, you will see which models rise to the top based on the metric you have selected for cross-validations...