Building a Recommendation System with Python 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
7/14/201712:00:00AM
Participants/Performers
Presenter: Lillian Pierson, P.E.
Description
Discover how to use Python to build programs that can make recommendations. This hands-on course explores different types of recommendation systems, and shows how to build each one.
Description
Discover how to use Python—and some essential machine learning concepts—to build programs that can make recommendations. In this hands-on course, Lillian Pierson, P.E. covers the different types of recommendation systems out there, and shows how to build each one. She helps you learn the concepts behind how recommendation systems work by taking you through a series of examples and exercises. Once you're familiar with the underlying concepts, Lillian explains how to apply statistical and machine learning methods to construct your own recommenders. She demonstrates how to build a popularity-based recommender using the Pandas library, how to recommend similar items based on correlation, and how to deploy various machine learning algorithms to make recommendations. At the end of the course, she shows how to evaluate which recommender performed the best.
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)
Pierson, P. (2017). Building a Recommendation System with Python Machine Learning & AI . linkedin.com.
Chicago / Turabian - Author Date Citation, 17th Edition (style guide)Pierson, P.E., Lillian. 2017. Building a Recommendation System With Python Machine Learning & AI. linkedin.com.
Chicago / Turabian - Humanities (Notes and Bibliography) Citation, 17th Edition (style guide)Pierson, P.E., Lillian. Building a Recommendation System With Python Machine Learning & AI linkedin.com, 2017.
MLA Citation, 9th Edition (style guide)Pierson, P.E. Building a Recommendation System With Python 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.
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Grouped Work ID
f2816785-8719-d3ef-2114-5db4060bdc78-eng
Grouping Information
Grouped Work ID | f2816785-8719-d3ef-2114-5db4060bdc78-eng |
---|---|
Full title | building a recommendation system with python machine learning and ai |
Author | pierson p e lillian |
Grouping Category | movie |
Last Update | 2024-04-15 10:54:20AM |
Last Indexed | 2024-04-28 01:18:23AM |
Book Cover Information
Image Source | sideload |
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First Loaded | Jul 17, 2022 |
Last Used | Apr 12, 2024 |
Marc Record
First Detected | Aug 03, 2021 02:25:10 PM |
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Last File Modification Time | Apr 15, 2024 11:02:12 AM |
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520 | |a Discover how to use Python to build programs that can make recommendations. This hands-on course explores different types of recommendation systems, and shows how to build each one. | ||
520 | |a Discover how to use Python—and some essential machine learning concepts—to build programs that can make recommendations. In this hands-on course, Lillian Pierson, P.E. covers the different types of recommendation systems out there, and shows how to build each one. She helps you learn the concepts behind how recommendation systems work by taking you through a series of examples and exercises. Once you're familiar with the underlying concepts, Lillian explains how to apply statistical and machine learning methods to construct your own recommenders. She demonstrates how to build a popularity-based recommender using the Pandas library, how to recommend similar items based on correlation, and how to deploy various machine learning algorithms to make recommendations. At the end of the course, she shows how to evaluate which recommender performed the best. | ||
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