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Smarter Data Science: Succeeding with Enterprise-Gra
US $29.69
大約HK$ 232.04
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狀況：
良好
曾被閱讀過的書籍，但狀況良好。封面有諸如磨痕等在內的極少損壞，但沒有穿孔或破損。精裝本書籍可能沒有書皮。封皮稍有磨損。絕大多數書頁未受損，存在極少的褶皺和破損。使用鉛筆標注文字處極少，未對文字標記，無留白處書寫文字。沒有缺頁。
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運送：
US $5.22（大約 HK$ 40.80） USPS Media MailTM.
所在地：New Orleans, Louisiana, 美國
送達日期：
估計於 8月28日 (星期四)至 9月4日 (星期四)之間送達 運送地點 94104
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物品細節
- 物品狀況
- Pages
- 304
- Publication Date
- 2020-06-03
- Subject Area
- Scientific Computing
- Educational Level
- Adult & Further Education
- Level
- Advanced
- Subject
- Science
- ISBN
- 9781119693413
- EAN
- 9781119693413
關於產品
Product Identifiers
Publisher
Wiley & Sons, Incorporated, John
ISBN-10
1119693411
ISBN-13
9781119693413
eBay Product ID (ePID)
12038435923
Product Key Features
Number of Pages
304 Pages
Language
English
Publication Name
Smarter Data Science : Succeeding with Enterprise-Grade Data and Ai Projects
Subject
Data Modeling & Design
Publication Year
2020
Type
Textbook
Subject Area
Computers
Format
Trade Paperback
Dimensions
Item Height
0.7 in
Item Weight
18.4 Oz
Item Length
9.1 in
Item Width
7.3 in
Additional Product Features
Intended Audience
Scholarly & Professional
Dewey Edition
23
Dewey Decimal
005.7
Synopsis
Organizations can make data science a repeatable, predictable tool, which business professionals use to get more value from their data Enterprise data and AI projects are often scattershot, underbaked, siloed, and not adaptable to predictable business changes. As a result, the vast majority fail. These expensive quagmires can be avoided, and this book explains precisely how. Data science is emerging as a hands-on tool for not just data scientists, but business professionals as well. Managers, directors, IT leaders, and analysts must expand their use of data science capabilities for the organization to stay competitive. Smarter Data Science helps them achieve their enterprise-grade data projects and AI goals. It serves as a guide to building a robust and comprehensive information architecture program that enables sustainable and scalable AI deployments. When an organization manages its data effectively, its data science program becomes a fully scalable function that's both prescriptive and repeatable. With an understanding of data science principles, practitioners are also empowered to lead their organizations in establishing and deploying viable AI. They employ the tools of machine learning, deep learning, and AI to extract greater value from data for the benefit of the enterprise. By following a ladder framework that promotes prescriptive capabilities, organizations can make data science accessible to a range of team members, democratizing data science throughout the organization. Companies that collect, organize, and analyze data can move forward to additional data science achievements: Improving time-to-value with infused AI models for common use cases Optimizing knowledge work and business processes Utilizing AI-based business intelligence and data visualization Establishing a data topology to support general or highly specialized needs Successfully completing AI projects in a predictable manner Coordinating the use of AI from any compute node. From inner edges to outer edges: cloud, fog, and mist computing When they climb the ladder presented in this book, businesspeople and data scientists alike will be able to improve and foster repeatable capabilities. They will have the knowledge to maximize their AI and data assets for the benefit of their organizations.
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賣家信用評價 （9,497）
- g***a (731)- 買家留下的信用評價。過去 1 個月購買已獲認證Thank you.
- t***t (603)- 買家留下的信用評價。過去 1 個月購買已獲認證Fast ship and book was as described. The gentlemen I buy these books for is really enjoying them! Thumbs up!
- t***o (424)- 買家留下的信用評價。過去 1 個月購買已獲認證Looks just fine