Machine learning using R

Examine the latest technological advancements in building a scalable machine-learning model with big data using R. This second edition shows you how to work with a machine-learning algorithm and use i

Core Insight：Cross-Domain Data Collaboration: Unlocking Chip PotentialEliminating the "efficiency gap" caused by knowledge silos is the starting point for industry potential. Data doesn't lie; Data Science provides the solution: Through innovation and cross-domain restructuring, we visualize results to become the critical accelerator for boosting efficiency.GenAI Reshaping the Future of SemiconductorsFacing the immense challenge of the slowing pace of Moore's Law, the semiconductor industry urgently requires new breakthroughs. This book is specifically designed to solve the "Efficiency Black Hole" that consumes tens of billions of dollars annually in the industry.The Empowering DTCO Innovation with AI and Machine Learning offers readers a practical DTCO.ML Framework, demonstrating how to leverage Machine Learning (ML) and Generative AI (GenAI) technologies to inject new acceleration into chip manufacturing processes. Learn to master process variability and optimize chip energy efficien

Examine business problems and use a practical analytical approach to solve them by implementing predictive models and machine learning techniques using SAS and the R analytical language. This bo

Carry out a variety of advanced statistical analyses including generalized additive models, mixed effects models, multiple imputation, machine learning, and missing data techniques using R. Each chapt

本書講解的是在R語言平臺上使用大數據技術構建可擴展機器學習模型的新技術成果。它全面展示了如何採用機器學習算法在原始數據的基礎上構建機器學習模型。本書還能讓那些希望利用ApacheHadoop、Hive、Pig和Spark來實現可擴展機器學習模型的讀者從中受益。

Become an expert in Bayesian Machine Learning methods using R and apply them to solve real-world big data problemsAbout This BookUnderstand the principles of Bayesian Inference with less mathematical

Written as a tutorial to explore and understand the power of R for machine learning. This practical guide that covers all of the need to know topics in a very systematic way. For each machine learning

Written as a tutorial to explore and understand the power of R for machine learning. This practical guide that covers all of the need to know topics in a very systematic way. For each machine learning

Gain insights into image-processing methodologies and algorithms, using machine learning and neural networks in Python. This book begins with the environment setup, understanding basic image-processing terminology, and exploring Python concepts that will be useful for implementing the algorithms discussed in the book. You will then cover all the core image processing algorithms in detail before moving onto the biggest computer vision library: OpenCV. You’ll see the OpenCV algorithms and how to use them for image processing. The next section looks at advanced machine learning and deep learning methods for image processing and classification. You’ll work with concepts such as pulse coupled neural networks, AdaBoost, XG boost, and convolutional neural networks for image-specific applications. Later you’ll explore how models are made in real time and then deployed using various DevOps tools. All the concepts in Practical Machine Learning and Image Processing are explained using r

如果你主要關注統計分析、數據可視化、線性代數、初等微積分，並希望較快上手，「R語言」會是較佳的選擇！本書獨特之處在於以直觀且實用的方式，清楚介紹人工智慧及機器學習領域中常用的管理數學工具。透過R語言的實作，讀者得以深入理解並實際應用於不同實務情境。書中的實例不侷限於理論探討，更著重實際應用，貼近日常生活，喚起讀者對數學的共鳴與學習熱情。舉例而言，透過應用貝氏定理，探討運動員實際服用興奮劑的真相，以及判斷過濾垃圾郵件的情境。同時，透過極佳化方法的應用，協助航空公司訂定最適價格和最大利潤路線圖等案例，使得理論更具實用性。除此之外，本書擴大管理數學的範疇：從管理數學傳統上僅處理統計、線性代數的刻板印象，將此核心概念延伸至線性轉換、特徵值與特徵向量等進階議題，並且更進一步涵蓋一般書籍較少觸及的「極佳化方法」，包括微分、極值、偏微分以及拉氏乘數等內容，於實用範例中為機器學習（Machine learning）的數學應用奠定基礎。線性規劃的討論更是引領讀者回溯至二戰時期，線性規劃應用於確定空中力量和雷達（radar）的最佳使用，具有時代非凡之意義。同時探討在各種混和限制條件下，欲達目標極大、極小化，使用線性代數中構築人工基底手法，自標準的極大化問題做為起點，經二階段法、對偶問題法、對偶單形法，深入解說 R 軟體 lpSolveAPI 套件背後的數學脈絡或故事。本書精彩內容 ——線性代數｜線性函數｜線性方程組｜矩陣｜向量空間｜線性轉換｜極佳化方法｜拉氏函數｜機率與統計｜單利．複利｜線性規劃｜馬可夫鏈｜預測｜本書特色☑ 以 R 軟體的程式語言與過程，深入解說並印證數學定義、定理☑ 透過 R 軟體的印證，經驗的移轉，形塑跨電腦語言的整體處理思維☑ 促成 R 軟體成為數學符號以外的第二語言，加速數學學習效率☑ 將人工智慧及機器學習常用之數學思維，應用於資料分析及解決管理問題

本書特色 ◆ 符合學測範圍！ 依據「高中英文參考詞彙表(111學年度起適用)」編寫，收錄Level 3~5學測必背單字，共100回。 Level 3：40回 Level 4：40回 Level 5 (精選Level 5高頻單字)：20回 ◆ 補充詳盡！ 補充常用搭配詞、同反義字及片語，有利舉一反三、輕鬆延伸學習範圍。 ◆ 配套豐富！ 隨書贈送 (1) 習題本附冊(100回) 一回一卷。讀完單字就能即時檢測實力。 (2) 電子朗讀音檔 由專業外籍錄音員錄製，獨家採「拼讀」方式錄音，(core，c-o-r-e，core，核心)，用聽覺輔助記憶。 下載請至「三民．東大音檔網」https://elearning.sanmin.com.tw/Voice/ (3) 英文三民誌2.0 APP 免費下載。隨時隨地培養核心英文字彙力。 詳細使用方式請見書中介紹。

Marketing Science Using R 重點探討行銷科學領域 相關統計觀念及R語言 ※內容詳解行銷科學的應用‧ ※強化解決行銷領域的問題 ※配合豐富的行銷實例說明 ※輕鬆理解並有效解決問題 本書適用於對行銷科學方法感興趣的讀者，不管是有心進入行銷領域的資訊管理背景人士，或是尋找量化分析工具的行銷從業人員，提供了理論與實務的最佳參考書籍。 【本書特色】 *直指行銷科學領域的應用層面，以解

Reader beware! The biography of R. L. Stine, author of the hugely popular Goosebumps series, is a scary-good time!R. L. Stine began writing stories at the age of nine, after finding a typewriter in hi

Spectrum(R) Writing for grade 2 guides students through each step of the writing process as they write sentences, personal stories, fiction stories, descriptions, comparisons, how-to instructions, reports, opinions, and more. Spectrum(R) Writing workbooks guide students as they write for a variety of purposes, including writing to tell a story, writing to provide information, and writing to state an opinion. Lessons support current state standards. Step-by-step instructions help with planning, drafting, revising, proofreading, and sharing writing. A Writer’s Handbook reinforces grammar and language skills, and a complete Answer Key is included. Engaging, open-ended writing projects combined with standards-based learning make these workbooks an essential resource for school success. Spectrum, the best-selling workbook series, is proud to provide quality educational materials that support your students’ learning achievement and success.

Spectrum(R) Writing for grade 3 guides students through each step of the writing process as they write paragraphs, personal narratives, fiction stories, descriptive comparisons, news reports, how-to instructions, persuasive letters, and more. Spectrum(R) Writing workbooks guide students as they write for a variety of purposes, including writing to tell a story, writing to provide information, and writing to state an opinion. Lessons support current state standards. Step-by-step instructions help with planning, drafting, revising, proofreading, and sharing writing. A Writer’s Handbook reinforces grammar and language skills, and a complete Answer Key is included. Engaging, open-ended writing projects combined with standards-based learning make these workbooks an essential resource for school success. Spectrum, the best-selling workbook series, is proud to provide quality educational materials that support your students’ learning achievement and success.

Spectrum(R) Writing for grade 6 guides students through each step of the writing process as they write paragraphs, personal narratives, fiction stories, descriptive comparisons, outlines, research reports, persuasive arguments, and more. Spectrum(R) Writing workbooks guide students as they write for a variety of purposes, including writing to tell a story, writing to provide information, and writing to state an opinion. Lessons support current state standards. Step-by-step instructions help with planning, drafting, revising, proofreading, and sharing writing. A Writer’s Handbook reinforces grammar and language skills, and a complete Answer Key is included. Engaging, open-ended writing projects combined with standards-based learning make these workbooks an essential resource for school success. Spectrum, the best-selling workbook series, is proud to provide quality educational materials that support your students’ learning achievement and success.

Tackle the real-world complexities of modern machine learning with innovative, cutting-edge, techniquesAbout This BookFully-coded working examples using a wide range of machine learning libraries and

⊙系統性內容編排：章節難度由淺至深安排，循序漸進建構知識。⊙實務應用導向：透過案例，學習運用各種統計方法分析問題，並以R語言的統計程式套件，解決不同的統計模式，達到做中學的學習效果。⊙提供習題演練：各章節皆附有習題，學習成效輕鬆驗收。【以R語言學習統計，邊做邊學好懂易上手】本書以R語言作為統計學教學的嚮導，運用R語言之程式套件中世界各地實際的研究個案與資料，讓學習者認識各種統計方法，解決不同的統計模式，也能了解統計在各方面的應用。書中章節安排難度由淺至深，循序漸進帶領學習者一一攻克各種統計方法，內容包含：R語言基礎指令操作、單變數資料、兩個與多個變數資料、機率、離散型機率分配、連續型機率分配、抽樣分配、常態近似與自助抽樣法、估計、統計假說檢定、變異數分析：多個母體平均數比較、簡單線性迴歸分析、多元線性迴歸分析、適合度檢定：類別資料分析、無母數統計等。各章節最末提供習題，讓學習者可透過演練驗收學習成效，加深記憶、鞏固知識。

適合程式設計新手，迅速進入資料科學領域。資料匯入、整理、變換、視覺化與模型建立。使用R和RStudio進行資料科學研究，利用tidyverse套件使工作更高效、流暢。這一版介紹Tidyverse的最新功能和最佳實務做法，並新增章節介紹從不同來源獲取資料，進一步實踐所學。「這本書更新了世界首屈一指的R資料科學實務指南，優秀程度令人驚歎，凡是與資料打交道的人都應該閱讀此書！」—Emma RandUniversity of York, UK運用R將資料轉化為洞察力、知識和理解。透過這本實用的書籍，有志於成為資料科學家的讀者將學會如何使用R和RStudio進行資料科學研究，並利用tidyverse這組專為協同工作而設計的套件，讓資料科學實務變得更快速、流暢且有趣。即使沒有程式設計的經驗，本書最新版也能幫助你迅速進入資料科學的領域。你將學會如何匯入、變換和視覺化資料，並傳達結果。你還將獲得資料科學流程的整體理解，以及管理細節所需的基本工具。這一版針對最新的tidyverse功能和最佳實務做法進行了更新，有新的章節示範如何從試算表、資料庫和網站獲取資料。其中的習題也將幫助你實踐所學。你將學到如何：‧視覺化：為資料探索和結果的交流創建圖表‧變換：找出變數型別及處理它們的工具‧匯入：將資料匯入R並轉換為方便分析的形式‧程式設計：學習R語言的工具，以更清晰的方式輕鬆解決資料問題‧溝通：使用Quarto整合說明、程式碼和分析結果

本書針對在行為科學界中，想以 R 著手進階統計分析的讀者而撰寫。第二版大幅改寫 R 程式，採用整齊資料（tidy）有關的資料整理套件與繪圖，並搭配管線運算子（pipe operator）。本書每一章皆以真實的案例為資料來源，實際演示資料分析一系列的歷程，使讀者更容易熟悉資料分析與 R 程式的使用。• 全部以精選之臺灣實際資料示範。• 分析流程完整，包括探索資料、設定模型分析與診斷模型三個步驟。• 所有分析可以完全重製。適用課程︰「統計軟體應用」、「統計模型應用」、「資料分析」等相關課程。適用對象︰大學、技專校院相關學系大學部、研究所之學生，亦適合實務工作者。

如何運用資料說故事？資料科學最重要的功能在於解讀與呈現其意義。將資料產生的意義加以串接與形成更多理解世界的線索，並且讓他們的讀者更快、更精準地理解現象背後的真相。自周敦頤說「文，所以載道也」，後有「文以載道」一說。對資料科學家，「文以載道」就是資料寫作學：讓資料分析成為書寫。如果文件需要對資料作圖表處理和統計分析，用R Markdown 製作文件就是最佳選擇。編輯R Markdown可以直接在R Studio當中進行，在寫R Code分析數據的同時，同時撰寫分析報告，不需要在不同的軟體中進行切換，上手相當容易。在本書中，將使用RStudio的免費平台，建立好讀者製表、製圖與繪製地圖的基本功，以及運用Markdown語法，將R語法及結果直接與你的解讀編織(knit) 在一起，進而轉為簡報檔或一本線上圖書。分享、讓大眾理解數據資料蘊含的脈絡與現象，是資料寫作最大的價值。

Welcome to the LEGO (R) Dreamzzz (TM) universe! Build your Mateo minifigure before joining him on an epic adventure to protect the dream world from the evil Nightmare King.

Little children will have fun using the wipe-clean pen as they solve pet-themed mazes, join dots, spot differences and trace over pictures and numbers. At the same time, they will be practising the vital pen-control skills they need for learning to write letters and numbers. The ink easily rubs off the shiny pages to make the activities ready to be done time and time again.

此套碼會以散裝單本出貨，包含以下書籍：9781645141662Social and Emotional Learning Activities, Grades Prek-K9781645141679Social and Emotional Learning Activities, Grades 1-29781645141686Social and Emotional Learning Activities, Grades 3-49781645141693Social and Emotional Learning Activities, Grades 5-6

Python機器學習第三版（上） Python Machine Learning - Third Edition 第三版－最新修訂版，新增TensorFlow 2、GAN和強化學習等實用內容 使用Python的scikit-learn和TensorFlow 2融會貫通機器學習與深度學習 循序漸進、由淺入深，好評熱銷再進化！最新修訂的《Python機器學習第三版》是一本不容錯過的全方位指南，也是讀者

Your home is the perfect place for learning, fun, and sibling bonding!The Happy Learning Book for Siblings features 50 hands-on activities you can conduct in the comfort of your home. They are divided

Count to ten and race to launch your rocket first with this interactive learning game from Scholastic Early Learners! An innovative, math-focused learning game complete with QR-code guidance. Provides

有效的資料分析、統計與繪圖實用錦囊 “和其它的程式語言書籍相比，我從這本書中學到更多。” ―David Curran Cognitive Engineer at OpenJaw Technologies 本書是《R錦囊妙計》第二版，擴展了更多的內容，使用R快速有效地執行超過275種實用資料分析。R語言提供了統計分析工作所需要的一切工具，但是它的結構可能有點難以掌握。本書彙整精簡、任務導向的錦囊，能

本書《R語言與資料分析實戰》以R語言的「程式設計屬性」為中心，內容涵蓋R語言基礎理論到實際資料分析，透過分析模型和演算法等更實用的範例，講解了資料視覺化、統計分析、資料採擷、機器學習等常用的方法。同時書中還收錄了作者的實戰經驗和學習體會，可以解決資料統計分析過程中出現的各種問題。如果你是一名資料統計分析的研究人員，本書將是一本不可多得的參考書，能夠深化理解與認識R軟體的應用，進一步提高資料統計分析

‧本書主要針對人文社科學子，以及有興趣以R分析民意調查資料的學習者所打造。以多種民意調查進行資料分析實作，包含大型面訪調查資料、電話調查資料及網路調查資料，從資料描述到報表輸出，都能用R輕鬆完成。•提供清楚的學習路徑圖，幫助三種學習者快速上手：無論如何都想入門R，卻苦無任何程式訓練背景的學習者、正在不同資料分析工具之間評估R的學習者，以及準備好要用R處理民意調查資料的學生、從業人員或是學者。•提供

What do you think is the most amazing machine in the universe? A superconductor? The modern computer? A rocket ship? Think again: It’s the human body!Astonishingly intricate and complex, your body gro

Modern statistical methods allow the analyst to fit and assess models as well as to undertake supervised or unsupervised learning to extract information. Contemporary data science requires tight integ

INTRODUCTIONSelf-Access Language Learning (SALL) has played a prominent part in language education in universities. Its role is to foster autonomous learning among students. With the wide-spread imple

This book introduces Raspberry Pi, using real world applications in computer vision, machine learning, and deep learning. It provides a detailed, step-by-step, approach to application development for

Master the essential skills needed to recognize and solve complex problems with machine learning and deep learning. Using real-world examples that leverage the popular Python machine learning ecosyste

This book develops a machine-learning framework for predicting economic growth. It can also be considered as a primer for using machine learning (also known as data mining or data analytics) to answer

By teaching you how to code machine-learning algorithms using a test-driven approach, this practical book helps you gain the confidence you need to use machine learning effectively in a business envir

※請確定您所選購之期刊正確無誤，本期為2026年4月-5月號　NO.239※※因雜誌到貨日期不一，請於下單時在備註欄填上您欲購買之期號(過期雜誌恕不接受訂購)※※本期號上架時間至2026/05/30※C o v e r S t o r y020 RADO 雷達表 Anatom Skeleton 當人體工學遇見鏤空機械 S p e c i a l T o p i c038 HUBLOT 宇舶 經典融合歐足超級聯賽計時碼錶S p e c i a l R e p o r t 042 PATEK PHILIPPE Nautilus 誕生50周年 全能運動錶的當代座標046 以詩意譜寫時間節奏 梵克雅寶《Poetry of Tim 時間的詩篇》展覽050 酒桶錶殼化身絕佳舞台 FRANCK MULLER 三款藝術家聯名錶款074 海洋上的時間競賽 ROLEX 與帆船運動的精神共鳴078 澳門先聲 時間成形 愛彼錶2026 年新作搶先鑑賞098 L'ÉCOLE 珠寶藝術學院打造可親近的珠寶藝術文化M a j o r R e p o r t082 腕錶設計來自世界的輪廓與色彩New Launches010 全球新錶速遞Watch Gallery028 水光之下 讀見鋒芒Talk Time040 MB&F 創辦人/ 總監Maximilian BüsserHot Stuff060 RICHARD MILLE / CHOPARD / URWERK / HERMÈS / ULYSSE NARDIN /HUBLOT / BREITLING / RESSENCE / MONTBLANC / LONGINESGlobal News & Events100 全球新聞快報