What topics are covered in 'An Introduction to Statistical Learning'?

The book covers a wide range of topics including linear regression, classification, resampling methods, shrinkage methods, tree-based methods, support vector machines, and more. Each chapter offers theoretical concepts followed by practical applications using R. This makes it ideal for students and professionals looking to enhance their statistical modeling skills, providing both foundational knowledge and advanced analytical techniques for real-world data. The application of R in examples ensures that readers gain hands-on experience with statistical learning.

Who is the target audience for this book?

This book is aimed at data scientists, statisticians, and graduate students in statistics and related fields. It provides a comprehensive introduction to statistical learning, making it suitable for beginners to intermediate users who wish to deepen their understanding. By combining theoretical aspects with practical examples, it enhances the learning experience for educators and practitioners alike. Readers can utilize the text as a course textbook or a self-study guide to navigate the world of statistical learning.

How does this book differ from other statistical learning texts?

Unlike many statistical learning texts that can be dense and overly complex, this book emphasizes clarity and practical application. It provides straightforward explanations of concepts, alongside practical examples and R code snippets. Such an approach makes statistical learning accessible and easier to comprehend, catering to both theoretical insights and practical application. This makes the book a go-to resource for those looking to bridge the gap between theory and real-world usage.

Can I use R packages with the examples in the book?

Yes, the book is designed to work seamlessly with various R packages, which enhance the practical learning experience. Each chapter includes code examples that illustrate how to implement statistical techniques using popular R packages, such as 'caret', 'randomForest', and 'ggplot2'. This integration allows readers to directly apply what they've learned in R, making it ideal for practicing data analysis and visualization in a hands-on manner.

Is there any supplementary material available for this book?

Yes, accompanying the second edition, there are various resources available online including datasets used in the examples, R code snippets, and additional exercises. These resources can typically be found on the publisher's website or related academic repositories. This supplementary material enriches the learning experience, enabling readers to further engage with the content and apply their knowledge to practical problems in statistical learning.

What is the importance of statistical learning in data science?

Statistical learning is crucial for data science as it underpins many popular machine learning algorithms. It provides the methodologies for understanding and predicting patterns in data, which is essential for actionable insights. By mastering statistical learning techniques, data analysts and scientists can build predictive models, perform data-driven decision-making, and uncover trends that inform strategic business choices. This skill set is increasingly valuable in various industries, from healthcare to finance.

Is this book suitable for self-study?

Absolutely! The book is structured to facilitate self-study, featuring clear explanations, illustrative examples, and exercises at the end of each chapter. Readers can learn at their own pace, utilizing the practices alongside explanations to develop their skills in statistical learning. It serves as a complete guide for individuals interested in independently enhancing their knowledge base and technical skills in the field, leveraging R for practical applications.

What prior knowledge is needed to read this book?

While the book can be approached with a basic understanding of statistics and R, it is beneficial for readers to have a foundational knowledge of linear algebra and probability theory. This background allows readers to more effectively grasp the content and context of statistical learning techniques. However, the book also introduces concepts progressively, making it accessible for those willing to learn and engage with new material along the way.

Are there case studies included in the book?

Yes, 'An Introduction to Statistical Learning' includes real-world case studies that illustrate the application of statistical methods to complex problems. These case studies help readers understand the relevance and effectiveness of statistical learning techniques in various fields. By examining these cases, readers can see how to implement theoretical concepts in practice, enhancing their ability to tackle real datasets and derive meaningful conclusions from their analyses.

كيف تتسوق An Introduction to Statistical Learning: with عبر الانترنت من يوباى?

من السهل التسوق في An Introduction to Statistical Learning: with عبر الإنترنت من يوباي. كل ما عليك فعله هو البحث عن المنتج واختيار طريقة الشحن الخاصة بك أثناء الدفع وسيتم توصيله الى عنوانك

هل An Introduction to Statistical Learning: with متوفر للتسوق عبر الإنترنت في Oman؟

نعم ، في يوباي Oman هذا المنتج متاح لك للتسوق بسعر مناسب. An Introduction to Statistical Learning: with غير متوفر محليًا ولكن يمكنك الوثوق بنا بخدماتنا للشحن السريع.

كم من الوقت يستغرق الحصول على المنتج بعد تقديم الطلب؟

يختلف وقت تسليم المنتج الذي طلبته حسب ما طلبته وطريقة الشحن التي اخترتها. يتم ذكر وقت التسليم المقدر أثناء عملية الدفع ، لذا كن مرتاحًا أثناء التسوق.

عرض الأصل

An Introduction to Statistical Learning: with Applications in R (Springer Texts in Statistics)

An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning with relevant applications and tutorial on implementing analyses and methods in R, targeted at statisticians and non-statisticians alike.

منتج #: 32827607

An Introduction to Statistical Learning: with Applications in R (Springer Texts in Statistics)

Q: Where can I buy 'An Introduction to Statistical Learning: with Applications in R'?

You can purchase 'An Introduction to Statistical Learning: with Applications in R' on Ubuy. Ubuy offers access to a variety of textbooks including this one, providing a convenient platform to browse and order the title directly from the comfort of your home. With a user-friendly interface, Ubuy simplifies the process of acquiring educational materials for those looking to enhance their knowledge in statistical learning.

منتج #: 32827607

OMR 32

تفاصيل السعر

باستثناء رسوم الشحن والجمارك ( سيتم احتساب رسوم الشحن والجمارك عند إتمام الشراء )

^{*سيتم استيراد جميع العناصر من أمريكا}

التوافر : متوفر فى المخزون

مستورد من متجر USA

كمية:

اطلب الآن واحصل عليه حول الخميس, أكتوبر 01

معاملة آمنة

أفضل شركائنا اللوجستيين

An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning with relevant applications and tutorial on implementing analyses and methods in R, targeted at statisticians and non-statisticians alike.

كفالة يو كير:

لا شيء

اختر الباقة

شحن
سريع

استرجاع
مجاني^*

تغليف آمن

منتجات أصلية %100

الامتثال لمعيار PCI DSS

حاصل على شهادة ISO 27001

Note: Step Down Voltage Transformer required for using electronics products of أمريكا store (110-120). Recommended power converters اشتري الآن.

تفاصيل المنتج

Accessible overview of statistical learning for analyzing complex datasets
Covers important modeling and prediction techniques with real-world applications
Includes tutorials on implementing analyses and methods in R
Written for statisticians and non-statisticians interested in statistical learning
Second edition features new chapters on deep learning, survival analysis, and multiple testing
R code updated for compatibility

Publisher	Springer
Publication date	July 30, 2021
Edition	Second Edition 2021
Language	English
Print length	622 pages
ISBN-10	1071614177
ISBN-13	978-1071614174
Item Weight	2.63 pounds (1.19 kg)
Dimensions	6.5 x 1.25 x 9.5 inches (16.5 x 3.2 x 24.1 cm)
Part of series	Springer Texts in Statistics

وصف المنتج

An Introduction to Statistical Learning: with Applications in R (Springer Texts in Statistics)

هل لديك أي استفسار؟ تحدث معنا

Product Buying Guide

An Introduction to Statistical Learning: with Applications in R is a comprehensive book that provides an accessible overview of statistical learning, a critical toolset for analyzing complex data sets. It covers various modeling and prediction techniques, including linear regression, classification, resampling methods, tree-based methods, and more. This guide aims to help potential buyers understand the product specifications, key features, usage scenarios, competitors, user reviews, price analysis, and buying considerations.

Product Specifications

Title: An Introduction to Statistical Learning: with Applications in R
Edition: 2nd Edition, 2021
Author: Gareth James, Daniela Witten, Trevor Hastie, and Robert Tibshirani
Publisher: Springer
Number of Pages: Varies
Language: English
Compatible Software: R

Key Features

Accessible overview of statistical learning techniques
Includes real-world examples and color graphics to illustrate methods
Provides tutorials on implementing analyses using R
Covers various important modeling and prediction techniques
New chapters on deep learning, survival analysis, and multiple testing in the second edition

Usage Scenarios

For practitioners in various fields (biology, finance, marketing, etc.) who need to analyze complex data sets
Suitable for both statisticians and non-statisticians
Requires only a previous course in linear regression
No knowledge of matrix algebra is required

Conclusion

An Introduction to Statistical Learning: with Applications in R is a valuable resource for anyone interested in statistical learning techniques. With its accessible approach, real-world examples, and tutorials on implementing analyses using R, it is suitable for both statisticians and non-statisticians. The second edition includes new chapters on deep learning, survival analysis, and multiple testing, making it even more comprehensive. Whether you are a practitioner in various fields or someone looking to expand their statistical knowledge, this book is a must-have.

عرض أقل

أسئلة العملاء & الإجابات

سؤال: كيف تتسوق An Introduction to Statistical Learning: with عبر الانترنت من يوباى?

إجابه: من السهل التسوق في An Introduction to Statistical Learning: with عبر الإنترنت من يوباي. كل ما عليك فعله هو البحث عن المنتج واختيار طريقة الشحن الخاصة بك أثناء الدفع وسيتم توصيله الى عنوانك
سؤال: هل An Introduction to Statistical Learning: with متوفر للتسوق عبر الإنترنت في Oman؟

إجابه: نعم ، في يوباي Oman هذا المنتج متاح لك للتسوق بسعر مناسب. An Introduction to Statistical Learning: with غير متوفر محليًا ولكن يمكنك الوثوق بنا بخدماتنا للشحن السريع.
سؤال: كم من الوقت يستغرق الحصول على المنتج بعد تقديم الطلب؟

إجابه: يختلف وقت تسليم المنتج الذي طلبته حسب ما طلبته وطريقة الشحن التي اخترتها. يتم ذكر وقت التسليم المقدر أثناء عملية الدفع ، لذا كن مرتاحًا أثناء التسوق.

Intelligence & Semantics Editorial Review

The book is highly recommended for beginners who want to learn about machine learning. It provides a clear and concise introduction to statistical learning and covers various methods in depth. The explanations are remarkably simple, making complex ideas easy to understand. While the book primarily uses R for programming, the focus is on understanding the inner workings of AI algorithms rather than training predictive models. The book strikes a good balance between theory and practical application. However, some readers may find the small print font size and slightly smaller dimensions of the hardcopy disappointing. Overall, this is a valuable resource for both beginners and experienced data scientists interested in statistics, data, and AI.

مراجعات العملاء وتقييماتهم

4.0

1 تقييمات العملاء

5 نجمة

0%
4 نجمة

100%
3 نجمة

0%
2 نجمة

0%
1 نجمة

0%

أضف تقييم لهذا المنتج

شارك أفكارك مع عملاء آخرين

إيجابيات

Clear and concise introduction to statistical learning
Simple explanations of complex ideas
Covers a variety of methods in depth
Good balance between theory and practical application

سلبيات

Uses R for programming, which may not be preferred by some readers

تاريخ سعر المنتج

معلومات مهمة

القيود: بالنسبة للمنتجات التي يتم شحنها دولياً، يُرجى ملاحظة أن أي ضمان من الشركة المصنعة قد لا يكون صالحاً؛ قد لا تتوفر خيارات خدمة الشركة المصنعة؛ قد لا تكون أدلة المنتج والتعليمات وتحذيرات السلامة مكتوبة بلغة بلد المقصد؛ قد لا يتم تصميم المنتجات (والمواد المصاحبة لها) وفقاً لمعايير بلد الوجهة والمواصفات ومتطلبات الملصقات؛ وقد لا تتوافق المنتجات مع الجهد الكهربي المستخدم في بلد الوجهة والمعايير الكهربائية الأخرى (تتطلب استخدام محوّل كهربي أو جهاز تحويل إذا كان ذلك مناسباً). المستلم مسؤول عن ضمان إمكانية استيراد المنتج بشكل قانوني إلى بلد الوجهة. عند الطلب من يوباي أو الشركات التابعة لها، يكون المستلم هو المستورد المسجل ويجب أن يلتزم بجميع القوانين واللوائح الخاصة ببلد الوجهة.
ليست كل المنتجات المدرجة على يوباي معروضة للبيع، لأن يوباي هو محرك بحث عالمي. المنتجات تخضع للوائح التصدير / التجارة.

OMR 32

اطلب الآن واحصل عليه حول الخميس, أكتوبر 01

كمية:

معاملة آمنة

نوفر لك مدفوعات مشفّرة، وحماية متكاملة للمشتري، مع الالتزام بمعايير PCI DSS وشهادة ISO 27001:2022 لضمان أعلى مستويات الأمان في كل عملية شراء.

أفضل شركائنا اللوجستيين

أسرع توصيل عبر الحدود

المميزات والفوائد

Accessible overview of statistical learning
Relevant applications and tutorial on implementing analyses and methods in R
Targeted at statisticians and non-statisticians alike
New chapters on deep learning, survival analysis, and multiple testing
Expanded treatments of naïve Bayes and generalized linear models
R code updated for compatibility

ضمان Ubuy

تسوّق بثقة مع منتجات أصلية %100، ومدفوعات آمنة متوافقة مع معيار PCI DSS، وحماية بيانات معتمدة وفق ISO 27001، وشحن دولي سريع، وإرجاع مجاني^*، وتغليف آمن لكل طلب.

An Introduction to Statistical Learning: with Applications in R (Springer Texts in Statistics)

OMR 32

شحن سريع

استرجاع مجاني*

تغليف آمن

منتجات أصلية %100

الامتثال لمعيار PCI DSS

حاصل على شهادة ISO 27001

تفاصيل المنتج

وصف المنتج

Product Buying Guide

Product Specifications

Key Features

Usage Scenarios

Conclusion

أسئلة العملاء & الإجابات

Intelligence & Semantics Editorial Review

مراجعات العملاء وتقييماتهم

أضف تقييم لهذا المنتج

إيجابيات

سلبيات

تاريخ سعر المنتج

معلومات مهمة

OMR 32

المميزات والفوائد

ضمان Ubuy

شحن
سريع

استرجاع
مجاني^*