Regularization in deep learning

Regularization in Deep Learning teaches you how to improve your model performance with a toolbox of regularization techniques. It covers both well-established regularization methods and groundbreaking modern approaches. Each technique is introduced using graphics, illustrations, and step-by-step cod...

Full description

Saved in:
Bibliographic Details
Main Author: LIU, Peng
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2024
Subjects:
Online Access:https://ink.library.smu.edu.sg/lkcsb_research/7202
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Singapore Management University
Language: English
id sg-smu-ink.lkcsb_research-8201
record_format dspace
spelling sg-smu-ink.lkcsb_research-82012024-06-07T08:22:19Z Regularization in deep learning LIU, Peng Regularization in Deep Learning teaches you how to improve your model performance with a toolbox of regularization techniques. It covers both well-established regularization methods and groundbreaking modern approaches. Each technique is introduced using graphics, illustrations, and step-by-step coding walkthroughs that make complex math easy to follow. You’ll learn how to augment your dataset with random noise, improve your model’s architecture, and apply regularization in your optimization procedures. You’ll soon be building focused deep learning models that avoid sprawling complexity and deliver more accurate results even with new or messy data sets. 2024-12-01T08:00:00Z text https://ink.library.smu.edu.sg/lkcsb_research/7202 Research Collection Lee Kong Chian School Of Business eng Institutional Knowledge at Singapore Management University Categorical Data Analysis Finance and Financial Management
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Categorical Data Analysis
Finance and Financial Management
spellingShingle Categorical Data Analysis
Finance and Financial Management
LIU, Peng
Regularization in deep learning
description Regularization in Deep Learning teaches you how to improve your model performance with a toolbox of regularization techniques. It covers both well-established regularization methods and groundbreaking modern approaches. Each technique is introduced using graphics, illustrations, and step-by-step coding walkthroughs that make complex math easy to follow. You’ll learn how to augment your dataset with random noise, improve your model’s architecture, and apply regularization in your optimization procedures. You’ll soon be building focused deep learning models that avoid sprawling complexity and deliver more accurate results even with new or messy data sets.
format text
author LIU, Peng
author_facet LIU, Peng
author_sort LIU, Peng
title Regularization in deep learning
title_short Regularization in deep learning
title_full Regularization in deep learning
title_fullStr Regularization in deep learning
title_full_unstemmed Regularization in deep learning
title_sort regularization in deep learning
publisher Institutional Knowledge at Singapore Management University
publishDate 2024
url https://ink.library.smu.edu.sg/lkcsb_research/7202
_version_ 1814047589415256064