Conceptual Variable Design for Scorecards: A Standardized Methodology for the Model-Building Process
暫譯: 得分卡的概念變數設計：模型建構過程的標準化方法論

Zapiain, Saul Rodrigo Alvarez

Conceptual Variable Design for Scorecards: A Standardized Methodology for the Model-Building Process
  • 出版商: Apress
  • 出版日期: 2025-07-01
  • 售價: $2,580
  • 貴賓價: 9.5 折 $2,451
  • 語言: 英文
  • 頁數: 732
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 9798868814204
  • ISBN-13: 9798868814204

    • 尚未上市，無法訂購

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商品描述

Embark on a journey through the intricate landscape of predictive modeling, where the fusion of conceptual clarity and robust statistical techniques creates powerful tools for decision-making. This book distills years of experience into a standardized methodology that empowers professionals across industries--from banking to telecommunications--to construct scorecards that predict outcomes with precision and confidence.

In a world driven by data, the ability to transform complex information into actionable insights is paramount. This is your essential guide to mastering the art and science of model building. With practical examples, real-world case studies, and step-by-step guidance, this book is not just a resource--it's a roadmap to success in the rapidly evolving field of analytics. By focusing on reducing operational risk, you'll be equipped to make informed decisions that safeguard your organization's future.

Whether you're a seasoned data scientist or just starting your journey, Conceptual Variable Design for Scorecards will provide you with the knowledge and skills to thrive in an era where data-driven decisions are the key to competitive advantage. Join the ranks of forward-thinking professionals who are redefining the future of risk management and predictive analytics. Your journey begins here.

What You Will Learn

    Harness the power of conceptualization to create models that solve real-world problems. Design meaningful variables that reflect the behaviors of your target population. Expand variables with temporal patterns to capture trends and dynamic changes. Master data integration to streamline preparation and avoid common pitfalls. Implement a unified workflow to simplify and accelerate the modeling process. Explore a larger number of variables in your multivariable models by harnessing the use of experimental design and hyperoptimization.

Who This Book Is For

Professionals engaged in the practical construction of models who seek to gain a comprehensive understanding of the model-building process.

商品描述(中文翻譯)

踏上預測建模的複雜景觀之旅，在這裡，概念的清晰與穩健的統計技術的融合創造出強大的決策工具。本書將多年經驗提煉成一套標準化的方法論，使各行各業的專業人士——從銀行業到電信業——能夠構建精確且可靠的預測評分卡。

在一個以數據驅動的世界中，將複雜信息轉化為可行見解的能力至關重要。這是您掌握模型構建藝術與科學的必備指南。透過實用範例、真實案例研究和逐步指導，本書不僅僅是資源——它是通往快速發展的分析領域成功的藍圖。專注於降低操作風險，您將能夠做出明智的決策，保障您組織的未來。

無論您是經驗豐富的數據科學家還是剛開始您的旅程，評分卡的概念變數設計將為您提供在數據驅動決策成為競爭優勢關鍵的時代中茁壯成長所需的知識和技能。加入那些重新定義風險管理和預測分析未來的前瞻性專業人士的行列。您的旅程從這裡開始。

您將學到什麼


  • 利用概念化的力量創建解決現實問題的模型。

  • 設計反映目標人群行為的有意義變數。

  • 擴展具有時間模式的變數，以捕捉趨勢和動態變化。

  • 掌握數據整合，以簡化準備過程並避免常見陷阱。

  • 實施統一的工作流程，以簡化和加速建模過程。

  • 通過利用實驗設計和超優化，探索多變量模型中的更多變數。

本書適合誰

從事模型實際構建的專業人士，尋求全面了解模型構建過程。

作者簡介

Saul Rodrigo Alvarez Zapiain brings over two decades of diverse professional experience to his role as a principal analytical consultant at SAS. His journey began with a bachelor's degree in industrial biochemical engineering, followed by a master's degree specializing in mathematical modeling of cellular organisms. Having started his career in industries such as pharma, telco, and market research, Saul transitioned to analytics, and while working at Santander, he discovered data mining, sparking a continuous quest for knowledge in analytical domains.

Around 16 years ago, while working at Santander, Saul discovered data mining, sparking a continuous quest for knowledge in analytical domains. Over the years, he honed his skills through self-education and numerous SAS courses, earning over 10 certifications, including Certified Data Scientist and Certified Professional in AI, Machine Learning, and Data Curation. Delving into specialized statistical techniques, he developed a deep understanding of the modeling process. It wasn't until Saul was invited to present his expertise at a conference organized by the Customer Success division that he fully recognized his niche--building models. This realization, coupled with his wealth of real-life experiences, shaped his approach to analytics and problem-solving.

作者簡介(中文翻譯)

Saul Rodrigo Alvarez Zapiain 擔任 SAS 的首席分析顧問，擁有超過二十年的多元專業經驗。他的旅程始於工業生化工程的學士學位，隨後獲得專攻細胞生物體數學建模的碩士學位。Saul 的職業生涯始於製藥、電信和市場研究等行業，之後轉向分析領域。在桑坦德銀行工作期間，他發現了資料探勘，這激發了他在分析領域持續追求知識的熱情。

大約在 16 年前，Saul 在桑坦德銀行工作時發現了資料探勘，這激發了他在分析領域持續追求知識的熱情。多年來，他透過自學和參加多個 SAS 課程來磨練自己的技能，獲得了超過 10 項證照，包括認證資料科學家和人工智慧、機器學習及資料管理的專業認證。深入研究專業統計技術後，他對建模過程有了深刻的理解。直到 Saul 被邀請在客戶成功部門舉辦的會議上展示他的專業知識時，他才完全意識到自己的專長——建模。這一認識，加上他豐富的實際經驗，塑造了他對分析和問題解決的看法。

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