Machine Learning: Make Your Own Recommender System (notice n° 78882)
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fixed length control field | 02984cam a2200277zu 4500 |
003 - CONTROL NUMBER IDENTIFIER | |
control field | FRCYB88953901 |
005 - DATE AND TIME OF LATEST TRANSACTION | |
control field | 20250108003726.0 |
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
fixed length control field | 250108s2024 fr | o|||||0|0|||eng d |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
International Standard Book Number | 9781835882061 |
035 ## - SYSTEM CONTROL NUMBER | |
System control number | FRCYB88953901 |
040 ## - CATALOGING SOURCE | |
Original cataloging agency | FR-PaCSA |
Language of cataloging | en |
Transcribing agency | |
Description conventions | rda |
100 1# - MAIN ENTRY--PERSONAL NAME | |
Personal name | Theobald, Oliver |
245 01 - TITLE STATEMENT | |
Title | Machine Learning: Make Your Own Recommender System |
Remainder of title | Build Your Recommender System with Machine Learning Insights |
Statement of responsibility, etc. | ['Theobald, Oliver'] |
264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE | |
Name of producer, publisher, distributor, manufacturer | Packt Publishing |
Date of production, publication, distribution, manufacture, or copyright notice | 2024 |
300 ## - PHYSICAL DESCRIPTION | |
Extent | p. |
336 ## - CONTENT TYPE | |
Content type code | txt |
Source | rdacontent |
337 ## - MEDIA TYPE | |
Media type code | c |
Source | rdamdedia |
338 ## - CARRIER TYPE | |
Carrier type code | c |
Source | rdacarrier |
520 ## - SUMMARY, ETC. | |
Summary, etc. | Launch into machine learning with our course and learn to create advanced recommender systems, ensuring ethical use and maximizing user satisfaction.Key FeaturesNavigate Scikit-Learn effortlesslyCreate advanced recommender systemsUnderstand ethical AI developmentBook DescriptionWith an introductory overview, the course prepares you for a deep dive into the practical application of Scikit-Learn and the datasets that bring theories to life. From the basics of machine learning to the intricate details of setting up a sandbox environment, this course covers the essential groundwork for any aspiring data scientist. The course focuses on developing your skills in working with data, implementing data reduction techniques, and understanding the intricacies of item-based and user-based collaborative filtering, along with content-based filtering. These core methodologies are crucial for creating accurate and efficient recommender systems that cater to the unique preferences of users. Practical examples and evaluations further solidify your learning, making complex concepts accessible and manageable. The course wraps up by addressing the critical topics of privacy, ethics in machine learning, and the exciting future of recommender systems. This holistic approach ensures that you not only gain technical proficiency but also consider the broader implications of your work in this field. With a final look at further resources, your journey into machine learning and recommender systems is just beginning, armed with the knowledge and tools to explore new horizons.What you will learnBuild data-driven recommender systemsImplement collaborative filtering techniquesApply content-based filtering methodsEvaluate recommender system performanceAddress privacy and ethical considerationsAnticipate future recommender system trendsWho this book is forThis course is ideal for aspiring data scientists and technical professionals with a basic understanding of Python programming and a keen interest in machine learning. This course lays the groundwork for those looking to specialize in building sophisticated recommender systems. |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical term or geographic name entry element | |
700 0# - ADDED ENTRY--PERSONAL NAME | |
Personal name | Theobald, Oliver |
856 40 - ELECTRONIC LOCATION AND ACCESS | |
Access method | Cyberlibris |
Uniform Resource Identifier | <a href="https://international.scholarvox.com/netsen/book/88953901">https://international.scholarvox.com/netsen/book/88953901</a> |
Electronic format type | text/html |
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