What is the primary focus of the 'Machine Learning 2nd Edition' book?

The 'Machine Learning 2nd Edition' primarily focuses on introducing the fundamental concepts and techniques in machine learning through detailed explanations and practical examples. It emphasizes both supervised and unsupervised learning methods, providing insights into algorithms, model evaluation, and real-world applications. This resource is ideal for students and professionals alike, as it balances theoretical foundations with hands-on programming exercises. By engaging with the book, readers can develop a robust understanding of various learning algorithms that empower them to apply these concepts in data science projects.

Who is the author of 'Machine Learning 2nd Edition'?

The author of 'Machine Learning 2nd Edition' is Christopher M. Bishop, a renowned expert in the field of machine learning. He has substantial academic credentials and practical experience, making this book a reliable source for learning advanced concepts and techniques. Bishop's comprehensive approach lets readers understand both classical methods and cutting-edge developments in machine learning, benefitting those who are new to the topic as well as seasoned practitioners. His ability to clarify complex topics ensures that every reader can grasp the essential principles of machine learning effectively.

Is 'Machine Learning 2nd Edition' suitable for beginners?

'Machine Learning 2nd Edition' is indeed suitable for beginners, as it provides a comprehensive overview of the basics before delving into more complex topics. The book starts with fundamental theories, gradually progressing to advanced algorithms, making it user-friendly for those unfamiliar with the subject. Additionally, it includes practical examples and exercises that enable beginners to apply their knowledge effectively. By utilizing this book, newcomers can build a strong foundation in machine learning concepts, which will prepare them for future studies or professional tasks in data science and analytics.

What makes 'Machine Learning 2nd Edition' stand out from other books?

'Machine Learning 2nd Edition' stands out due to its clear exposition of concepts, practical examples, and up-to-date coverage of contemporary machine learning techniques. Author Christopher M. Bishop integrates the latest research findings and trends into the text, making it relevant for both students and professionals seeking to understand current developments in the field. Moreover, its structured format, combining theory with practical application, allows readers to effectively grasp complex algorithms. This combination of clarity, depth, and practicality makes it a preferred choice among machine learning enthusiasts.

What programming languages are covered in 'Machine Learning 2nd Edition'?

'Machine Learning 2nd Edition' covers various programming languages, primarily focusing on Python and MATLAB for practical implementation of machine learning algorithms. Python, being one of the most widely-used languages in data science, is particularly emphasized as it offers a rich ecosystem of libraries such as NumPy, SciPy, and scikit-learn. The book includes examples and exercises that encourage readers to implement algorithms using these languages. By practicing with Python or MATLAB, learners can effectively reinforce their understanding and apply machine learning techniques in real-world scenarios.

What types of machine learning algorithms are discussed in this book?

'Machine Learning 2nd Edition' discusses a variety of machine learning algorithms, including decision trees, neural networks, support vector machines, and ensemble methods. The book thoughtfully categorizes these algorithms into supervised and unsupervised learning techniques, enabling readers to understand when and how to apply them effectively. Each section is complemented by practical examples, allowing readers to delve deeper into algorithmic implementations. With this comprehensive coverage, learners can explore different algorithmic approaches and choose the right one for their specific data analysis tasks.

Are there any exercises or problems included in 'Machine Learning 2nd Edition'?

'Machine Learning 2nd Edition' includes a wide array of exercises and problems that challenge readers to apply the theoretical knowledge they acquire throughout the text. Each chapter features carefully crafted exercises that reinforce learning through hands-on experience. Readers can engage with practical challenges that mirror real-world applications of machine learning. By completing these exercises, learners can solidify their understanding and gain confidence in their programming skills and algorithmic implementations, which is crucial for aspiring data scientists and machine learning practitioners.

How does 'Machine Learning 2nd Edition' address the latest trends in machine learning?

'Machine Learning 2nd Edition' addresses the latest trends in machine learning by discussing modern advancements such as deep learning, reinforcement learning, and natural language processing. The book includes examples from cutting-edge research, equipping readers with insights into current methodologies and practical applications. This contemporary perspective ensures that the content remains relevant and useful for both academic study and industry practice. By exploring these trends, readers are better prepared to contribute to innovative projects and understand ongoing developments in the rapidly evolving field of machine learning.

What are the practical applications of machine learning covered in this book?

'Machine Learning 2nd Edition' covers numerous practical applications ranging from image recognition, speech processing, and recommendation systems to predictive analytics in finance and healthcare. Each application is illustrated through real-world examples that contextualize the algorithms discussed. This practical focus helps readers understand how machine learning can be leveraged to solve everyday problems, enhancing their ability to utilize these techniques in various domains. By mastering these real-world applications, learners can effectively implement machine learning solutions in their fields of interest.

Where can I buy 'Machine Learning 2nd Edition' in Hong Kong?

You can buy 'Machine Learning 2nd Edition' in Hong Kong from Ubuy. Ubuy offers a convenient platform with a wide selection of books and educational resources, ensuring that you can easily find this title along with other machine learning literature. By choosing Ubuy, you can browse detailed product descriptions, read customer reviews, and enjoy a smooth purchasing experience that caters to your needs. With various payment options and user-friendly navigation, Ubuy makes it simple to obtain your copy of this essential machine learning resource.

如何從 Ubuy 在線購物 Machine Learning: A Bayesian and Optimization？

從 Ubuy 在線購物 Machine Learning: A Bayesian and Optimization 非常簡單。. 您只需搜索產品，在結賬時選擇運輸方式，然後將其運送到您所在的位置。

Machine Learning: A Bayesian and Optimization 可以在 Hong Kong 在線購物嗎？

是的，您可以在 Ubuy Hong Kong 以合理的價格購買該產品。. Machine Learning: A Bayesian and Optimization 在本地不可用，但您可以信任我們的快遞服務。

下訂單後需要多長時間才能收到產品？

您訂購的產品的交貨時間根據您訂購的商品和您選擇的運輸方式而有所不同。. 結賬時會提到預計送貨時間，所以購物時請放心。

觀看原文

Machine Learning: A Bayesian and Optimization Perspective

Machine Learning: A Bayesian and Optimization Perspective gives a unified perspective on machine learning by covering both pillars of supervised learning, namely regression and classification.

物品 #: 40617981

Machine Learning: A Bayesian and Optimization Perspective

88% of respondents would recommend this to a friend

物品 #: 40617981

HKD 1045

~~HKD 1104~~

Price Details

Excluding Shipping & Custom charges ( Shipping and custom charges will be calculated on checkout )

^{*All items will import from 美國}

您省下 : 7%

供應情形 : 有存貨

從USA商店導入

QTY:

現在訂購，約可在下列時間收貨：星期五, 十月 30

Secured transaction

Our Top Logistics Partners

Machine Learning: A Bayesian and Optimization Perspective gives a unified perspective on machine learning by covering both pillars of supervised learning, namely regression and classification.

U-Care Warranty:

None

選擇一個計劃

Fast
Shipping

Free
Return^*

Secure Packaging

100% Original Products

PCI DSS Compliance

ISO 27001 Certified

Note: Step Down Voltage Transformer required for using electronics products of 美國 store (110-120). Recommended power converters 立即購買.

What Stands Out

Updated Content

This edition includes the latest advancements in machine learning, ensuring readers are well-versed in cutting-edge techniques and applications within the rapidly evolving field.

Practical Examples

Offers real-world case studies and hands-on exercises, allowing readers to apply theoretical concepts and deepen their understanding of practical machine learning solutions.

Expert Author

Authored by renowned experts, this book provides authoritative insights and perspectives, making it a reliable resource for learners and professionals aiming to enhance their expertise.

產品詳情

Provides a unifying perspective on machine learning covering probabilistic and deterministic approaches based on optimization techniques and Bayesian inference
Suitable for various courses including pattern recognition, signal processing, Bayesian learning, sparse modeling, deep learning, and probabilistic graphical models
Covers major machine learning methods developed in disciplines such as statistics, signal processing, and computer science
Explains methods and techniques in depth, supported by examples and problems, making it valuable for students and researchers
Includes more simple examples on basic theory, rewrites of the Neural Networks and Deep Learning chapter, and expanded treatment of Bayesian learning

Publisher	Academic Press
Publication date	July 31, 2020
Edition	2nd
Language	English
Print length	1160 pages
ISBN-10	0128188030
ISBN-13	978-0128188033
Item Weight	5.4 pounds (2.45 kg)
Dimensions	7.5 x 2.25 x 9.25 inches (19.1 x 5.7 x 23.5 cm)

Who Should Buy?

Beginners in ML
Ideal for users new to machine learning, providing foundational concepts and practical approaches to start their journey.
Data Scientists
Useful for data scientists looking to enhance their understanding of advanced algorithms and practical applications in the field.
Academics & Researchers
Beneficial for academics seeking a comprehensive resource for teaching and conducting research in machine learning topics.

Advanced Practitioners
Not suitable for experienced professionals who already possess deep knowledge of machine learning concepts and techniques.

產品敘述

Machine Learning: A Bayesian and Optimization Perspective

有疑問？與我們聊天

客戶問題與解答

題: 如何從 Ubuy 在線購物 Machine Learning: A Bayesian and Optimization？

回答: 從 Ubuy 在線購物 Machine Learning: A Bayesian and Optimization 非常簡單。. 您只需搜索產品，在結賬時選擇運輸方式，然後將其運送到您所在的位置。
題: Machine Learning: A Bayesian and Optimization 可以在 Hong Kong 在線購物嗎？

回答: 是的，您可以在 Ubuy Hong Kong 以合理的價格購買該產品。. Machine Learning: A Bayesian and Optimization 在本地不可用，但您可以信任我們的快遞服務。
題: 下訂單後需要多長時間才能收到產品？

回答: 您訂購的產品的交貨時間根據您訂購的商品和您選擇的運輸方式而有所不同。. 結賬時會提到預計送貨時間，所以購物時請放心。

Signal Processing Editorial Review

Machine Learning: A Bayesian and Optimization Perspective is an essential resource for Machine Learning practitioners delving into the fundamentals of the field. The book offers clear diagrams and comprehensive content, spanning 1160 pages, making it suitable for graduate courses in machine learning. Readers note the effectiveness of the book, particularly appreciating its reference value alongside other texts in Bayesian machine learning. However, some critiques highlight the book's lack of colorful illustrations, which could enhance the understanding of complex mathematical concepts. Despite minor criticisms, it remains a highly recommended title for those serious about mastering machine learning concepts.

Customer Reviews & Ratings

4.0

1 客戶評分

5 星

0%
4 星

100%
3 星

0%
2 星

0%
1 星

0%

評價此產品

與其他客戶分享您的想法

優點

Comprehensive coverage of machine learning basics
Clear diagrams enhance understanding
Suitable for graduate-level courses
Strong reference point for Bayesian ML
High quality printing noted by readers

缺點

Lack of colorful illustrations in the content

Product Price History

重要資訊

限制：如跨國購買產品，請注意製造商的保固有可能無效；製造商服務選項可能無法使用；產品手冊、教學、以及安全警示可能不會是目的地國家的語言；產品（與附加材料）設計也許不會符合目的地國家的標準、規格、以及標示要求；且產品也許不會符合目的地國家的伏特數值與其他電力標準（需要使用合適的變壓器或轉接器）。收件者須負責確定該產品在目的地國家可合法進口。當在 Ubuy 或其聯盟夥伴網站上訂購時，收件者為記錄上的進口者，且必須遵從目的地國家的法律與規範。
由於 Ubuy 是一個全球搜尋引擎，並不是所有列於 Ubuy 的產品都有出售。產品須受出口／貿易法規規範。

HKD 1045

~~HKD 1104~~

現在訂購，約可在下列時間收貨：星期五, 十月 30

QTY:

Secured transaction

PCI DSS compliant and ISO 27001:2022 certified, with encrypted payments and full buyer protection on every order.

Our Top Logistics Partners

Fastest cross-border delivery

特色和優勢

Covers both regression and classification in machine learning.
Explains the physical reasoning behind mathematics, without sacrificing rigor.
Includes case studies and computer exercises.
Suitable for different courses: pattern recognition, statistical/adaptive signal processing, and statistical/Bayesian learning.
New edition includes updated chapter on Neural Networks and Deep Learning.
Expanded treatment of Bayesian learning to include nonparametric Bayesian methods.

Ubuy Assurance

Experience worry-free shopping with 100% original products, PCI DSS-compliant payment security, ISO 27001-certified data protection, the fastest cross-border delivery, free returns ^*, and secure packaging on every order.

Machine Learning: A Bayesian and Optimization Perspective

HKD 1045

Fast Shipping

Free Return*

Secure Packaging

100% Original Products

PCI DSS Compliance

ISO 27001 Certified

What Stands Out

產品詳情

Who Should Buy?

產品敘述

客戶問題與解答

Signal Processing Editorial Review

Customer Reviews & Ratings

評價此產品

優點

缺點

Product Price History

重要資訊

HKD 1045

特色和優勢

Ubuy Assurance

Fast
Shipping

Free
Return^*