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

Feature selection

The basic idea behind feature selection is to select features that show high importance for the target. In addition, we want to remove any features that are highly cross-correlated (or have high MI values) to other features. The selected set of features are represented as feature lists in DataRobot. If you click on the Feature Lists menu on the top left of the page, as shown in the following screenshot, you will see the feature lists that DataRobot has created for the dataset:

Figure 5.24 – Feature Lists

Here, you will see a list that contains all the raw features, ones that have selections based on univariate analysis (that is, analysis of features one at a time), and also ones that have the most important features. The DR Reduced Features M8 list or the Univariate Selections list look like good starting points. Click on the Project Data menu to go back to the data view. Now, let's inspect the univariate list by selecting Univariate...