國立虎尾科技大學 |

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

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Optimizing AI and machine learning solutions :/ Mirza Rahim Baig.
其他題名:	your ultimate guide to building high-impact ML/AI solutions /
作者:	Baig, Mirza Rahim.
面頁冊數:	1 online resource (394 pages)
標題:	COMPUTERS / Data Science / Machine Learning. -
電子資源:	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 /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:

1483854
COMPUTERS / Data Science / Machine Learning.
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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650 7 $a COMPUTERS / Data Science / Machine Learning. $2 bisacsh $3 1483854
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650 7 $a COMPUTERS / Artificial Intelligence / Natural Language Processing. $2 bisacsh $3 1483851
650 7 $a COMPUTERS / Computer Science. $2 bisacsh $3 1483847
655 4 $a Electronic books. $2 local $3 554714
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