Còn hàng
Discovering Knowledge in Data
Discovering Knowledge in Data
Discovering Knowledge in Data
Discovering Knowledge in Data
Discovering Knowledge in Data
Discovering Knowledge in Data
Discovering Knowledge in Data
Discovering Knowledge in Data

Discovering Knowledge in Data

Tình trạng: Còn hàng
Tác giả: Wiley
Loại: Data

Discovering Knowledge in Data refers to the process of extracting valuable insights and patterns from large datasets, often through techniques in data mining, predictive analytics, statistical analysis, and business intelligence. This field helps organizations leverage their existing databases to make informed decisions and enhance their operational strategies.

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📚📚 I. THÔNG TIN SẢN PHẨM
📒 Mã sản phẩm :  STT1142
📒 Nhà xuất bản : Wiley; 2nd edition (July 8, 2014)
📒 Tác giả : Daniel T. Larose, Chantal D. Larose
📒 ISBN      : 0470908742
📒 Số trang : 336  trang
📒 Hình thức : Bìa Mềm, in ĐEN TRẮNG
📒 Loại : Sách gia công đóng gáy keo chắc chắn chất lượng cao
📒 Giấy in : Giấy ngoại định lượng 70msg, viết vẽ và hightlight thoải mái.
📒 Chất lượng : Bản in rõ nét, giá rất tốt cho mọi người.


📚📚 II. MÔ TẢ SẢN PHẨM
📒 1.Mô tả sản phẩm

Thinking in Java has earned raves from programmers worldwide for its extraordinary clarity, careful organization, and small, direct programming examples. From the fundamentals of Java syntax to its most advanced features, Thinking in Java.

Thinking in Java is designed to teach, one simple step at a time : 
The classic object-oriented introduction for beginners and experts alike, fully updated for Java SE5/6 with many new examples and chapters!
Test framework shows program output.
Design patterns are shown with multiple examples throughout: Adapter, Bridge, Chain of Responsibility, Command, Decorator, Facade, Factory Method, Flyweight, Ite

 

📒 2. Tác giả

Daniel T. Larose earned his PhD in Statistics at the University of Connecticut. He is Professor of Mathematical Sciences and Director of the Data Mining programs at Central Connecticut State University.  His consulting clients have included Microsoft, Forbes Magazine, the CIT Group, KPMG International, Computer Associates, and Deloitte, Inc. This is Larose’s fourth book for Wiley.

Chantal D. Larose is an Assistant Professor of Statistics & Data Science at Eastern Connecticut State University (ECSU).  She has co-authored three books on data science and predictive analytics.  She helped develop data science programs at ECSU and at SUNY New Paltz.  She received her PhD in Statistics from the University of Connecticut, Storrs in 2015 (dissertation title: Model-based Clustering of Incomplete Data).

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