Skip to search
Skip to main content
Search in
Keyword
Title (keyword)
Author (keyword)
Subject (keyword)
Title starts with
Subject (browse)
Author (browse)
Author (sorted by title)
Call number (browse)
search for
Search
Advanced Search
Bookmarks
(
0
)
Princeton University Library Catalog
Start over
Cite
Send
to
SMS
Email
EndNote
RefWorks
RIS format (e.g. Zotero)
Printer
Bookmark
MACHINE LEARNING : a comprehensive beginner's guide akshay b. r....et al.
Format
Book
Language
English
Published/​Created
[S.l.] : CRC PRESS, 2024.
Description
1 online resource
Details
Subject(s)
Machine learning
[Browse]
Related name
R., Akshay B.
[Browse]
Summary note
Machine learning is a dynamic and rapidly expanding field focused on creating algorithms that empower computers to recognize patterns, make predictions and continually enhance performance. It enables computers to learn from data and experiences, making decisions without explicit programming. For learners, mastering the fundamentals of machine learning opens doors to a world of possibilities to build robust and accurate models. In the ever-evolving landscape of machine learning, datasets play a pivotal role in shaping its future. The field has been revolutionized with the introduction of oneAPI, which provides a unified programming model across different architectures, including CPUs, GPUs, FPGAs and accelerators, fostering an efficient and portable programming environment. Embracing this unified model empowers practitioners to build efficient and scalable machine learning solutions, marking a significant stride in cross-architecture development. Dive into this fascinating field to master machine learning concepts with the step-by-step approach outlined in this book and contribute to its exciting future.
Source of description
OCLC-licensed vendor bibliographic record.
ISBN
1-03-267668-X
9781032676685
OCLC
1434561099
Doi
10.1201/9781032676685
Statement on responsible collection description
Princeton University Library aims to describe library materials in a manner that is respectful to the individuals and communities who create, use, and are represented in the collections we manage.
Read more...
Other views
Staff view
Need Help?
Ask a Question
Suggest a Correction
Report a Missing Item
Supplementary Information