The Decision Maker's Handbook to Data Science: A Guide for Non-Technical Executives, Managers, and Founders
暫譯: 數據科學決策者手冊：非技術高管、經理及創始人的指南

Kampakis, Stylianos

The Decision Maker's Handbook to Data Science: A Guide for Non-Technical Executives, Managers, and Founders
  • 出版商: Apress
  • 出版日期: 2019-11-27
  • 售價: $1,770
  • 貴賓價: 9.5 折 $1,682
  • 語言: 英文
  • 頁數: 156
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 1484254937
  • ISBN-13: 9781484254936
  • 相關分類: Maker、Data Science

    • 海外代購書籍(需單獨結帳)

商品描述

Data science is expanding across industries at a rapid pace, and the companies first to adopt best practices will gain a significant advantage. To reap the benefits, decision makers need to have a confident understanding of data science and its application in their organization. It is easy for novices to the subject to feel paralyzed by intimidating buzzwords, but what many don't realize is that data science is in fact quite multidisciplinary--useful in the hands of business analysts, communications strategists, designers, and more.

With the second edition of The Decision Maker's Handbook to Data Science, you will learn how to think like a veteran data scientist and approach solutions to business problems in an entirely new way. Author Stylianos Kampakis provides you with the expertise and tools required to develop a solid data strategy that is continuously effective. Ethics and legal issues surrounding data collection and algorithmic bias are some common pitfalls that Kampakis helps you avoid, while guiding you on the path to build a thriving data science culture at your organization. This updated and revised second edition, includes plenty of case studies, tools for project assessment, and expanded content for hiring and managing data scientists

Data science is a language that everyone at a modern company should understand across departments. Friction in communication arises most often when management does not connect with what a data scientist is doing or how impactful data collection and storage can be for their organization. The Decision Maker's Handbook to Data Science bridges this gap and readies you for both the present and future of your workplace in this engaging, comprehensive guide.


What You Will Learn

  • Understand how data science can be used within your business.
  • Recognize the differences between AI, machine learning, and statistics.
  • Become skilled at thinking like a data scientist, without being one.
  • Discover how to hire and manage data scientists.
  • Comprehend how to build the right environment in order to make your organization data-driven.


Who This Book Is For

Startup founders, product managers, higher level managers, and any other non-technical decision makers who are thinking to implement data science in their organization and hire data scientists. A secondary audience includes people looking for a soft introduction into the subject of data science.


商品描述(中文翻譯)

資料科學正在各行各業迅速擴展，最早採用最佳實踐的公司將獲得顯著的優勢。為了獲得這些好處，決策者需要對資料科學及其在組織中的應用有信心的理解。對於初學者來說，面對令人畏懼的流行術語可能會感到無所適從，但許多人未意識到資料科學實際上是相當多學科的——在商業分析師、傳播策略師、設計師等手中都非常有用。

在第二版的《決策者資料科學手冊》中，您將學會如何像資深資料科學家一樣思考，並以全新的方式解決商業問題。作者Stylianos Kampakis提供了發展穩固資料策略所需的專業知識和工具，這些策略能夠持續有效。Kampakis幫助您避免一些常見的陷阱，例如資料收集和算法偏見的倫理和法律問題，同時指導您在組織中建立蓬勃發展的資料科學文化。這一更新和修訂的第二版包含了大量案例研究、項目評估工具以及擴展的內容，幫助您招聘和管理資料科學家。

資料科學是一種現代公司中每個部門都應該理解的語言。當管理層無法與資料科學家所做的工作或資料收集和存儲對組織的影響建立聯繫時，溝通中的摩擦最常發生。《決策者資料科學手冊》彌補了這一差距，並為您在這本引人入勝、全面的指南中做好當前和未來工作場所的準備。

您將學到的內容：
- 了解資料科學如何在您的業務中使用。
- 認識AI、機器學習和統計之間的差異。
- 學會像資料科學家一樣思考，而不必成為資料科學家。
- 探索如何招聘和管理資料科學家。
- 理解如何建立正確的環境，使您的組織以資料為驅動。

本書適合對象：
創業公司創始人、產品經理、高層管理人員以及任何考慮在其組織中實施資料科學並招聘資料科學家的非技術決策者。次要讀者包括希望對資料科學主題有輕鬆入門的人士。

作者簡介

Dr. Stylianos (Stelios) Kampakis is a data scientist who lives and works in London, UK. He holds a PhD in Computer Science from University College London, as well as an MSc in Informatics from the University of Edinburgh. He also holds degrees in Statistics, Cognitive Psychology, Economics and Intelligent Systems. He is a member of the Royal Statistical Society and an honorary research fellow in the UCL Centre for Blockchain Technologies. He has many years of academic and industrial experience in all fields of data science like statistical modelling, machine learning, classic AI, optimization and more.

Throughout his career, Stylianos has been involved in a wide range of projects: from using deep learning to analyze data from mobile sensors and radar devices, to recommender systems, to natural language processing for social media data to predicting sports outcomes. He has also done work in the areas of econometrics, Bayesian modelling, forecasting and research design. He also has many years of experience in consulting for startups and scale-ups, having successfully worked with companies of all stages, some of which have raised millions of dollars in funding. He is still providing services in data science and blockchain, as a partner in Electi Consulting.

In the academic domain, he is one of the foremost experts in the area of sports analytics, having done his PhD in the use of machine learning for predicting football injuries. He has also published papers in the areas neural networks, computational neuroscience and cognitive science. Finally, he is also involved in blockchain research and more specifically in the areas of tokenomics, supply chains and securitization of assets.

Stylianos is also very active in the area of data science education. He is the founder of The Tesseract Academy, a company whose mission is to help decision makers understand deep technical topics such as machine learning and blockchain. He is also teaching "Social Media Analytics", and "Quantitative Methods and Statistics with R" in the Cyprus International Institute of Management, and runs his own data science school in London called Datalyst.

He often writes about data science, machine learning, blockchain and other topics at his personal blog: The Data Scientist (thedatascientist.com).


作者簡介(中文翻譯)

Stylianos (Stelios) Kampakis 博士 是一位數據科學家，居住並在英國倫敦工作。他擁有倫敦大學學院的計算機科學博士學位，以及愛丁堡大學的資訊學碩士學位。他還擁有統計學、認知心理學、經濟學和智能系統的學位。他是英國皇家統計學會的成員，並且是倫敦大學學院區塊鏈技術中心的榮譽研究員。他在數據科學的各個領域擁有多年學術和工業經驗，包括統計建模、機器學習、經典人工智慧、優化等。

在他的職業生涯中，Stylianos 參與了各種項目：從使用深度學習分析來自移動傳感器和雷達設備的數據，到推薦系統，再到社交媒體數據的自然語言處理以及預測體育賽事結果。他還在計量經濟學、貝葉斯建模、預測和研究設計等領域進行過工作。他在初創企業和成長型企業的諮詢方面也有多年經驗，成功與各階段的公司合作，其中一些公司已籌集了數百萬美元的資金。他目前仍在 Electi Consulting 擔任合夥人，提供數據科學和區塊鏈的服務。

在學術領域，他是體育分析領域的頂尖專家之一，博士論文研究了使用機器學習預測足球受傷的問題。他還在神經網絡、計算神經科學和認知科學等領域發表過論文。最後，他還參與區塊鏈研究，特別是在代幣經濟學、供應鏈和資產證券化等領域。

Stylianos 在數據科學教育方面也非常活躍。他是 The Tesseract Academy 的創始人，該公司的使命是幫助決策者理解機器學習和區塊鏈等深奧的技術主題。他還在塞浦路斯國際管理學院教授「社交媒體分析」和「使用 R 的定量方法與統計」，並在倫敦經營自己的數據科學學校 Datalyst。

他經常在個人部落格 The Data Scientist (thedatascientist.com) 上撰寫有關數據科學、機器學習、區塊鏈和其他主題的文章。

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