Industrial Machine Learning: Using Artificial Intelligence as a Transformational Disruptor

Vermeulen, Andreas Francois

  • 出版商: Apress
  • 出版日期: 2019-12-01
  • 定價: $2,200
  • 售價: 9.0$1,980
  • 語言: 英文
  • 頁數: 637
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 1484253159
  • ISBN-13: 9781484253151
  • 相關分類: 人工智慧Machine Learning
  • 立即出貨 (庫存 < 3)

商品描述

Understand the industrialization of machine learning (ML) and take the first steps toward identifying and generating the transformational disruptors of artificial intelligence (AI). You will learn to apply ML to data lakes in various industries, supplying data professionals with the advanced skills required to handle the future of data engineering and data science.

Data lakes currently generated by worldwide industrialized business activities are projected to reach 35 zettabytes (ZB) as the Fourth Industrial Revolution produces an exponential increase of volume, velocity, variety, variability, veracity, visualization, and value. Industrialization of ML evolves from AI and studying pattern recognition against the increasingly unstructured resource stored in data lakes.

Industrial Machine Learning supplies advanced, yet practical examples in different industries, including finance, public safety, health care, transportation, manufactory, supply chain, 3D printing, education, research, and data science. The book covers: supervised learning, unsupervised learning, reinforcement learning, evolutionary computing principles, soft robotics disruptors, and hard robotics disruptors.


What You Will Learn

  • Generate and identify transformational disruptors of artificial intelligence (AI)
  • Understand the field of machine learning (ML) and apply it to handle big data and process the data lakes in your environment
  • Hone the skills required to handle the future of data engineering and data science


Who This Book Is For

Intermediate to expert level professionals in the fields of data science, data engineering, machine learning, and data management


商品描述(中文翻譯)

了解機器學習(ML)的工業化,並踏出第一步,開始辨識和生成人工智慧(AI)的轉型破壞者。您將學習將ML應用於各行各業的數據湖,為數據專業人員提供處理未來數據工程和數據科學所需的高級技能。

目前由全球工業化商業活動生成的數據湖預計將達到35個ZB,隨著第四次工業革命對數據湖中存儲的體積、速度、多樣性、變異性、真實性、可視化和價值的指數級增長,ML的工業化從AI和對越來越無結構資源的模式識別研究中演變而來。

《工業機器學習》提供了不同行業的高級實例,包括金融、公共安全、醫療保健、交通運輸、製造業、供應鏈、3D打印、教育、研究和數據科學。本書涵蓋了監督學習、無監督學習、強化學習、演化計算原理、軟機器人破壞者和硬機器人破壞者。

您將學到什麼:
- 生成和辨識人工智慧(AI)的轉型破壞者
- 了解機器學習(ML)領域,並應用於處理大數據和處理您環境中的數據湖
- 磨練處理未來數據工程和數據科學所需的技能

適合閱讀對象:
- 在數據科學、數據工程、機器學習和數據管理領域具有中級到專家級專業水平的專業人士

作者簡介

Andreas François Vermeulen is Chief Data Scientist and Solutions Delivery Manager at Sopra-Steria and he serves as part-time doctoral researcher and senior research project advisor at University of St. Andrews on future concepts in health care systems, Internet of Things (IoT) sensors, massive distributed computing, mechatronics, at-scale data lake technology, data science, business intelligence (BI), and deep machine learning in health informatics.

Andre maintains and incubates the Rapid Information Factory data processing framework. He is active in developing next-generation data processing frameworks and mechatronics engineering with over 36 years of global experience in complex data processing, software development, and system architecture. He is an expert data scientist, doctoral trainer, corporate consultant, and speaker/author/columnist on data science, business intelligence, machine learning, decision science, data engineering, distributed computing, and at-scale data lakes. He has expert-level industrial experience in various areas (finance, telecommunication, manufacturing, government service, public safety and health informatics).

Andre received his bachelor's degree from North West University at Potchefstroom, his Master of Business Administration (MBA) at University of Manchester, his Master of Business Intelligence and Data Science degree at University of Dundee, and his Doctor of Philosophy at University of St. Andrews.

作者簡介(中文翻譯)

Andreas François Vermeulen是Sopra-Steria的首席數據科學家和解決方案交付經理,同時也是聖安德魯斯大學的兼職博士研究員和高級研究項目顧問,研究領域包括醫療保健系統的未來概念、物聯網(IoT)傳感器、大規模分散式計算、機電一體化、大規模數據湖技術、數據科學、商業智能(BI)和健康信息學中的深度機器學習。

Andreas維護並孵化Rapid Information Factory數據處理框架。他在複雜數據處理、軟件開發和系統架構方面擁有36年的全球經驗,積極參與下一代數據處理框架和機電一體化工程的開發。他是一位專業的數據科學家、博士培訓師、企業顧問,並在數據科學、商業智能、機器學習、決策科學、數據工程、分散式計算和大規模數據湖等領域擔任演講者、作者和專欄作家。他在金融、電信、製造、政府服務、公共安全和健康信息學等多個領域擁有專業級的工業經驗。

Andreas在Potchefstroom的北西大學獲得學士學位,曼徹斯特大學獲得工商管理碩士(MBA)學位,丹地大學獲得商業智能和數據科學碩士學位,聖安德魯斯大學獲得哲學博士學位。