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  Author: creativelivenew1   |   15 September 2024   |   Comments icon: 0
Data–Driven Innovation for Intelligent Technology Perspectives and Applications in ICT (Studies in Big Data, 148)
Free Download Data-Driven Innovation for Intelligent Technology: Perspectives and Applications in ICT (Studies in Big Data, 148) by Hiram Ponce, Jorge Brieva, Octavio Lozada-Flores
English | April 17, 2024 | ISBN: 3031542762 | 258 pages | MOBI | 16 Mb

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  Author: creativelivenew1   |   15 September 2024   |   Comments icon: 0
Data–Driven HR How to Use AI, Analytics and Data to Drive Performance, 2nd Edition
Free Download Data-Driven HR: How to Use AI, Analytics and Data to Drive Performance, 2nd Edition by Bernard Marr
English | December 3rd, 2023 | ISBN: 1398614564 | 240 pages | True EPUB | 1.42 MB
How can HR professionals utilize and leverage their organization's data effectively, with the use of AI, for more talent attraction, better employee engagement and higher talent retention to ultimately drive performance?

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  Author: creativelivenew1   |   15 September 2024   |   Comments icon: 0
Data and Applications Security and Privacy XXXVI
Free Download Shamik Sural, Haibing Lu, "Data and Applications Security and Privacy XXXVI"
English | 2022 | ISBN: 3031106830 | PDF | pages: 330 | 14.6 mb
This book constitutes the refereed proceedings of the 36th Annual IFIP WG 11.3 Conference on Data and Applications Security and Privacy, DBSec 2022, held in Newark, NJ, USA, in July 2022.

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  Author: creativelivenew1   |   15 September 2024   |   Comments icon: 0
Data Structures and Algorithms (DSA) Tutorial  Data Structures and Algorithms for Beginners
Free Download Data Structures and Algorithms (DSA) Tutorial : Data Structures and Algorithms for Beginners by Kavishankar Panchtilak
English | 2024 | ISBN: B0CW1DWH65 | 187 pages | MOBI | 28 Mb
Why to Learn Data Structures & Algorithms (DSA)? As applications are getting complex and data rich, there are three common problems that applications face now-a-days. Data Search − Consider an inventory of 1 million(106) items of a store. If the application is to search an item, it has to search an item in 1 million(106) items every time slowing down the search. As data grows, search will become slower. Processor speed − Processor speed although being very high, falls limited if the data grows to a billion records. Multiple requests − As thousands of users can search data simultaneously on a web server, even the fast server fails while searching the data. To solve the above-mentioned problems, data structures come to the rescue. Data can be organised in a data structure in such a way that all items may not be required to be searched, and the required data can be searched almost instantly.

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  Author: creativelivenew1   |   15 September 2024   |   Comments icon: 0
Data Structure in Python
Free Download Data Structure in Python: From Basics to Expert Proficiency
by William Smith

English | August 4, 2024 | ISBN: 0000616818 | 258 pages | EPUB | 0.82 Mb

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  Author: creativelivenew1   |   15 September 2024   |   Comments icon: 0
Data Structure and Algorithms in Java
Free Download Data Structure and Algorithms in Java: From Basics to Expert Proficiency
by William Smith

English | August 3, 2024 | ISBN: 000061677X | 256 pages | EPUB | 0.86 Mb

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  Author: creativelivenew1   |   15 September 2024   |   Comments icon: 0
Data Modeling with Microsoft Power BI Self–Service and Enterprise Data Warehouses with Power BI
Free Download Data Modeling with Microsoft Power BI: Self-Service and Enterprise Data Warehouses with Power BI by Markus Ehrenmueller-Jensen
English | July 16th, 2024 | ISBN: 109814855X | 485 pages | True PDF | 15.54 MB
Data modeling is the single most overlooked feature in Power BI Desktop, yet it's what sets Power BI apart from other tools on the market. This practical book serves as your fast-forward button for data modeling with Power BI, Analysis Services tabular, and SQL databases. It serves as a starting point for data modeling, as well as a handy refresher.

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  Author: creativelivenew1   |   15 September 2024   |   Comments icon: 0
Data Modeling with Microsoft Power BI Self–Service and Enterprise Data Warehouse with Power BI
Free Download Data Modeling with Microsoft Power BI: Self-Service and Enterprise Data Warehouse with Power BI by Markus Ehrenmueller-Jensen
English | July 16th, 2024 | ISBN: 109814855X | 482 pages | True EPUB (Retail Copy) | 12.77 MB
Data modeling is the single most overlooked feature in Power BI Desktop, yet it's what sets Power BI apart from other tools on the market. This practical book serves as your fast-forward button for data modeling with Power BI, Analysis Services tabular, and SQL databases. It serves as a starting point for data modeling, as well as a handy refresher.

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  Author: creativelivenew1   |   15 September 2024   |   Comments icon: 0
Data Labeling in Machine Learning with Python Explore modern ways to prepare labeled data
Free Download Data Labeling in Machine Learning with Python: Explore modern ways to prepare labeled data for training and fine-tuning ML and generative AI models by Vijaya Kumar Suda
English | January 31, 2024 | ISBN: 1804610542 | 398 pages | PDF | 37 Mb
Take your data preparation, machine learning, and GenAI skills to the next level by learning a range of Python algorithms and tools for data labelingKey FeaturesGenerate labels for regression in scenarios with limited training dataApply generative AI and large language models (LLMs) to explore and label text dataLeverage Python libraries for image, video, and audio data analysis and data labelingPurchase of the print or Kindle book includes a free PDF eBookBook Description

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  Author: creativelivenew1   |   15 September 2024   |   Comments icon: 0
Data Integration The Relational Logic Approach
Free Download Michael Genesereth, "Data Integration: The Relational Logic Approach "
English | ISBN: 3031004221 | 2010 | 112 pages | PDF | 2 MB
Data integration is a critical problem in our increasingly interconnected but inevitably heterogeneous world. There are numerous data sources available in organizational databases and on public information systems like the World Wide Web. Not surprisingly, the sources often use different vocabularies and different data structures, being created, as they are, by different people, at different times, for different purposes. The goal of data integration is to provide programmatic and human users with integrated access to multiple, heterogeneous data sources, giving each user the illusion of a single, homogeneous database designed for his or her specific need. The good news is that, in many cases, the data integration process can be automated. This book is an introduction to the problem of data integration and a rigorous account of one of the leading approaches to solving this problem, viz., the relational logic approach. Relational logic provides a theoretical framework for discussing data integration. Moreover, in many important cases, it provides algorithms for solving the problem in a computationally practical way. In many respects, relational logic does for data integration what relational algebra did for database theory several decades ago. A companion web site provides interactive demonstrations of the algorithms. Table of Contents: Preface / Interactive Edition / Introduction / Basic Concepts / Query Folding / Query Planning / Master Schema Management / Appendix / References / Index / Author Biography Don't have access? Recommend our Synthesis Digital Library to your library or purchase a personal subscription. Email [email protected] for details.

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