Dive into deep learning/ Aston Zhang, Zachary C. Lipton, Pennsylvania), Mu Li, and Alexander J. Smola.

By:

Zhang, Aston [author.]

Contributor(s):

Material type: Text

TextPublisher: Cambridge, United Kingdom ; New York, NY : Cambridge University Press, [2024]Description: xxxi, 548 pages : illustrations (chiefly color) ; 26 cmContent type:

text

Media type:

unmediated

Carrier type:

volume

ISBN:

9781009389426
1009389424
9781009389433
1009389432

Subject(s):

DDC classification:

006.31 ZAD 23

LOC classification:

Q325.73 .Z43 2024

Summary: "This approachable text teaches all the concepts, the context, and the code needed to understand deep learning. Suitable for students and professionals, the book doesn't require any previous background in machine learning or deep learning. Interactive examples feature throughout, with runnable code and executable Jupyter notebooks available online"-- Provided by publisher.

Average rating: 0.0 (0 votes)

Holdings
Item type	Current library	Collection	Call number	Copy number	Status	Date due	Barcode
Books	Main library	Computers & Information Technology ( Computer Science )	006.31 ZAD (Browse shelf(Opens below))	C.1	Available		00017706

Browsing Main library shelves Close shelf browser (Hides shelf browser)

Previous					No cover image available			Next
Previous	006.31 SSM Machine Learning in Multimedia: Unlocking the Power of Visual and Auditory Intelligence/	006.31 T.S.M Machine learning : a Bayesian and optimization perspective /	006.31 WJM Model-Based Machine Learning/	006.31 ZAD Dive into deep learning/	006.312 A. The art and science of analyzing software data /	006.312 A.A.D Data analysis and data mining : an Introduction /	006.312 A.A.D Data analysis and data mining : an Introduction /	Next

Includes bibliographical references and index.

"This approachable text teaches all the concepts, the context, and the code needed to understand deep learning. Suitable for students and professionals, the book doesn't require any previous background in machine learning or deep learning. Interactive examples feature throughout, with runnable code and executable Jupyter notebooks available online"-- Provided by publisher.

There are no comments on this title.

to post a comment.