Spark for Machine Learning & AI.
(eVideo)

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Published
Carpenteria, CA linkedin.com, 2017.
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Format
eVideo
Language
English

Notes

General Note
11/07/201712:00:00AM
Participants/Performers
Presenter: Dan Sullivan
Summary
Discover the powerful Apache Spark platform for machine learning. Learn about preprocessing data, applying algorithms to a variety of machine learning problems, and more.
Summary
Apache Spark is one of the most widely used and supported open-source tools for machine learning and big data. In this course, discover how to work with this powerful platform for machine learning. Instructor Dan Sullivan discusses MLlib-the Spark machine learning library-which provides tools for data scientists and analysts who would rather find solutions to business problems than code, test, and maintain their own machine learning libraries. He shows how to use DataFrames to organize data structure, and he covers data preparation and the most commonly used types of machine learning algorithms: clustering, classification, regression, and recommendations. By the end of the course, you will have experience loading data into Spark, preprocessing data as needed to apply MLlib algorithms, and applying those algorithms to a variety of machine learning problems.
System Details
Latest version of the following browsers: Chrome, Safari, Firefox, or Internet Explorer. Adobe Flash Player Plugin. JavaScript and cookies must be enabled. A broadband Internet connection.

Citations

APA Citation, 7th Edition (style guide)

Sullivan, D. (2017). Spark for Machine Learning & AI . linkedin.com.

Chicago / Turabian - Author Date Citation, 17th Edition (style guide)

Sullivan, Dan. 2017. Spark for Machine Learning & AI. linkedin.com.

Chicago / Turabian - Humanities (Notes and Bibliography) Citation, 17th Edition (style guide)

Sullivan, Dan. Spark for Machine Learning & AI linkedin.com, 2017.

MLA Citation, 9th Edition (style guide)

Sullivan, Dan. Spark for Machine Learning & AI linkedin.com, 2017.

Note! Citations contain only title, author, edition, publisher, and year published. Citations should be used as a guideline and should be double checked for accuracy. Citation formats are based on standards as of August 2021.