【獨家發(fā)布】最新-商務數(shù)據(jù)科學 - 數(shù)據(jù)挖掘... ...，2013年(英文)【高清】

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【英美最新教材】《商務數(shù)據(jù)科學 - 數(shù)據(jù)挖掘... ...，2013年》（英文）【高清】
前言：
由于是2013年剛剛出版的嶄新書籍，現(xiàn)在是2013年9月22日。所以，很有可能涉及版權(quán)問題，特此通知大家，欲下從速。過了這個村，可能就沒有那個店了！這本書可是英美經(jīng)典書籍。
.
這本書：
英文書名：《Data Science for Business: What you need to know about data mining and data-analytic thinking》
2013年，408頁，PDF， 15.7 MB。
Language: English
這本書，目前在網(wǎng)上售價，相當于每本書人民幣220元。


詳情可見鏈接：http://www.amazon.co.uk/Data-Science-Business-data-analytic-thinking/dp/1449361323

簡介：
Written by renowned data science experts Foster Provost and Tom Fawcett, Data Science for Business introduces the fundamental principles of data science, and walks you through the "data-analytic thinking" necessary for extracting useful knowledge and business value from the data you collect. This guide also helps you understand the many data-mining techniques in use today.
Based on an MBA course Provost has taught at New York University over the past ten years, Data Science for Business provides examples of real-world business problems to illustrate these principles. You’ll not only learn how to improve communication between business stakeholders and data scientists, but also how participate intelligently in your company’s data science projects. You’ll also discover how to think data-analytically, and fully appreciate how data science methods can support business decision-making.
Understand how data science fits in your organization—and how you can use it for competitive advantage
Treat data as a business asset that requires careful investment if you’re to gain real value
Approach business problems data-analytically, using the data-mining process to gather good data in the most appropriate way
Learn general concepts for actually extracting knowledge from data
Apply data science principles when interviewing data science job candidates
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Data_Science_for_Business_What_you_need_to_know_about_data_mining_and_data-analy.pdf (15.75 MB, 需要: 5 個論壇幣)

2013-9-22 18:01:13 上傳

需要: 5 個論壇幣  [購買]

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Data Science for Business: What you need to know about data mining and data-analytic thinking

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