Sign In Start Free Trial
Account

Add to playlist

Create a Playlist

Modal Close icon
You need to login to use this feature.
  • Book Overview & Buying Agile Machine Learning with DataRobot
  • Table Of Contents Toc
Agile Machine Learning with DataRobot

Agile Machine Learning with DataRobot

By : Chadha, Juwe
4.8 (11)
close
close
Agile Machine Learning with DataRobot

Agile Machine Learning with DataRobot

4.8 (11)
By: Chadha, 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)
close
close
1
Section 1: Foundations
5
Section 2: Full ML Life Cycle with DataRobot: Concept to Value
11
Section 3: Advanced Topics

Machine learning algorithms

There are now hundreds of machine learning algorithms available to be used for a machine learning project, and more are being invented every day. DataRobot supports a wide array of open source machine learning algorithms, including several deep learning algorithms – Prophet, SparkML-based algorithms, and H2O algorithms. Let's now take a look at what types of algorithms exist and what they are used for (Figure 2.7):

Figure 2.7 – Machine learning algorithms

Our focus will mostly be on the algorithm types that DataRobot supports. These algorithm types are described in the following sub-sections.

Supervised learning

Supervised learning algorithms are used when you can provide an answer (also called a label) as part of the training dataset. For supervised learning, you have to assign a feature of your dataset to be the answer, and the algorithm tries to learn to predict the answer by seeing multiple examples and...

CONTINUE READING
83
Tech Concepts
36
Programming languages
73
Tech Tools
Icon Unlimited access to the largest independent learning library in tech of over 8,000 expert-authored tech books and videos.
Icon Innovative learning tools, including AI book assistants, code context explainers, and text-to-speech.
Icon 50+ new titles added per month and exclusive early access to books as they are being written.
Agile Machine Learning with DataRobot
notes
bookmark Notes and Bookmarks search Search in title playlist Add to playlist font-size Font size

Change the font size

margin-width Margin width

Change margin width

day-mode Day/Sepia/Night Modes

Change background colour

Close icon Search
Country selected

Close icon Your notes and bookmarks

Confirmation

Modal Close icon
claim successful

Buy this book with your credits?

Modal Close icon
Are you sure you want to buy this book with one of your credits?
Close
YES, BUY

Submit Your Feedback

Modal Close icon
Modal Close icon
Modal Close icon