Leverage DataRobot's enterprise AI platform and automated decision intelligence to extract business value from data
Key Features
- Get well-versed with DataRobot features using real-world examples
- Use this all-in-one platform to build, monitor, and deploy ML models for handling the entire production life cycle
- Make use of advanced DataRobot capabilities to programmatically build and deploy a large number of ML models
Book Description
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.
What you will learn
- Understand and solve business problems using DataRobot
- Use DataRobot to prepare your data and perform various data analysis tasks to start building models
- Develop robust ML models and assess their results correctly before deployment
- Explore various DataRobot functions and outputs to help you understand the models and select the one that best solves the business problem
- Analyze a model's predictions and turn them into actionable insights for business users
- Understand how DataRobot helps in governing, deploying, and maintaining ML models
Who this book is for
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, building, and deploying a broader range of models. The book assumes a basic understanding of machine learning.
Table of Contents
- What Is DataRobot and Why You Need It
- Machine Learning Basics
- Understanding and Defining Business Problems
- Preparing Data for DataRobot
- Exploratory Data Analysis with DataRobot
- Model Building with DataRobot
- Model Understanding and Explainability
- Model Scoring and Deployment
- Forecasting and Time Series Modeling
- Recommender Systems
- Working with Geospatial Data, NLP, and Image Processing
- DataRobot Python API
- Model Governance and MLOps
- Conclusion
Bipin Chadha is a hands-on leader of data science teams who can find innovative solutions to complex problems. He creates systemic data-driven models that enable executives to understand how their business operates, analyze a broad range of scenarios and strategies, and understand the likely implications of decisions and events prior to implementing risky changes. His passion is building data-driven cultures, developing effective teams, and driving organizations to grow and succeed. Sylvester Juwe is a highly accomplished Executive, with hands-on technical expertise implementing complex Big Data and Advanced Analytics solutions, from conceptualisation to commercial impact. He is a well versed leader who leverages sophisticated data capabilities, influences stakeholders, and creates a strong culture of governance and curiosity in solving complex business challenges, thereby creating commercial impact.
