國立虎尾科技大學 |

Optimizing AI and machine learning solutions = your ultimate guide to building high-impact ML/AI solutions /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Optimizing AI and machine learning solutions / Mirza Rahim Baig.
Reminder of title:	your ultimate guide to building high-impact ML/AI solutions /
Author:	Baig, Mirza Rahim.
Description:	1 online resource (394 pages)
Subject:	COMPUTERS / Computer Science. -
Online resource:	https://portal.igpublish.com/iglibrary/search/BPB0000590.html
ISBN:	9789355518859

Optimizing AI and machine learning solutions = your ultimate guide to building high-impact ML/AI solutions /
Baig, Mirza Rahim.

Optimizing AI and machine learning solutions your ultimate guide to building high-impact ML/AI solutions /[electronic resource] ：Mirza Rahim Baig. - 1 online resource (394 pages)

Includes bibliographical references and index.

Optimizing AI and machine learning solutions : your ultimate guide to building high-impact ML/AI solutions -- About the Author -- About the Reviewer -- Acknowledgement -- Preface -- Table of Contents -- Chapter 1. Optimizing a Machine Learning /Artificial Intelligence Solution -- Chapter 2. ML Problem Formulation: Setting the Right Objective -- Chapter 3. Data Collection and Pre-processing -- Chapter 4. Model Evaluation and Debugging -- Chapter 5. Imbalanced Machine Learning -- Chapter 6. Hyper-parameter Tuning -- Chapter 7. Parameter Optimization Algorithms -- Chapter 8. Optimizing Deep Learning Models -- Chapter 9. Optimizing Image Models -- Chapter 10. Optimizing Natural Language Processing Models -- Chapter 11. Transfer Learning -- Index.

Access restricted to authorized users and institutions.

This book approaches data science solution building using a principled framework and case studies with extensive hands-on guidance. It will teach the readers optimization at each step, whether it is problem formulation or hyperparameter tuning for deep learning models. This book keeps the reader pragmatic and guides them toward practical solutions by discussing the essential ML concepts, including problem formulation, data preparation, and evaluation techniques. Further, the reader will be able to learn how to apply model optimization with advanced algorithms, hyperparameter tuning, and strategies against overfitting. They will also benefit from deep learning by optimizing models for image processing, natural language processing, and specialized applications. The reader can put theory into practice with hands-on case studies and code examples, reinforcing their understanding. With this book, the reader will be able to create high-impact, high-value ML/AI solutions by optimizing each step of the solution building process, which is the ultimate goal of every data science professional.

Mode of access: World Wide Web.

ISBN: 9789355518859Subjects--Topical Terms:

1483847
COMPUTERS / Computer Science.
Index Terms--Genre/Form:

554714
Electronic books.

LC Class. No.: QA76.9.D343

Dewey Class. No.: 006.31

Optimizing AI and machine learning solutions = your ultimate guide to building high-impact ML/AI solutions /
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505 0 # $a Optimizing AI and machine learning solutions : your ultimate guide to building high-impact ML/AI solutions -- About the Author -- About the Reviewer -- Acknowledgement -- Preface -- Table of Contents -- Chapter 1. Optimizing a Machine Learning /Artificial Intelligence Solution -- Chapter 2. ML Problem Formulation: Setting the Right Objective -- Chapter 3. Data Collection and Pre-processing -- Chapter 4. Model Evaluation and Debugging -- Chapter 5. Imbalanced Machine Learning -- Chapter 6. Hyper-parameter Tuning -- Chapter 7. Parameter Optimization Algorithms -- Chapter 8. Optimizing Deep Learning Models -- Chapter 9. Optimizing Image Models -- Chapter 10. Optimizing Natural Language Processing Models -- Chapter 11. Transfer Learning -- Index.
506 # $a Access restricted to authorized users and institutions.
520 3 $a This book approaches data science solution building using a principled framework and case studies with extensive hands-on guidance. It will teach the readers optimization at each step, whether it is problem formulation or hyperparameter tuning for deep learning models. This book keeps the reader pragmatic and guides them toward practical solutions by discussing the essential ML concepts, including problem formulation, data preparation, and evaluation techniques. Further, the reader will be able to learn how to apply model optimization with advanced algorithms, hyperparameter tuning, and strategies against overfitting. They will also benefit from deep learning by optimizing models for image processing, natural language processing, and specialized applications. The reader can put theory into practice with hands-on case studies and code examples, reinforcing their understanding. With this book, the reader will be able to create high-impact, high-value ML/AI solutions by optimizing each step of the solution building process, which is the ultimate goal of every data science professional.
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655 # 4 $a Electronic books. $2 local $3 554714
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