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

Understanding the results

In this section, we will discuss various visualizations of metrics and other information to understand the results of the modeling exercise. These are important visualizations that need to be inspected carefully in addition to looking at the model metrics discussed in the previous section. These visualizations are generated automatically by DataRobot for any model that it trains.

Lift chart

The lift chart shows how effective the model is at predicting the target values. As the number of data points is typically very large to show in one graphic, the lift chart sorts the output and aggregates the data into multiple bins. It then compares the averages of predictions and actuals in each bin (Figure 2.13):

Figure 2.13 – Lift chart

The preceding lift chart shows how the predictions have been sorted from low to high and then binned (60 bins in this case). You can now see the average prediction and average actual value in each...