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

Using the DataRobot Python client

The Python programming language is one of the most popular programming languages used by data scientists. It is flexible yet powerful. Being able to integrate the AutoML capabilities of DataRobot and utilize the flexibility of Python offers data scientists various benefits, as we mentioned earlier.

Programming in Python using the Jupyter IDE.

Now, let's explore the DataRobot Python client.

To use the DataRobot Python client, Python must be version 2.7 or 3.4+. The most up-to-date version of DataRobot must be installed. For the cloud version, the pip command will install the most recent version of the DataRobot package. On Python, running !pip install datarobot should install the DataRobot package.

Having installed the DataRobot package, the package has been imported. The Client method of the DataRobot package provides the much-needed connection to the DataRobot instance. As shown in Figure 12.3, the basic format for the Client...