Tag: Graph

Disk Graph 3.0.3 macOS


Free Download Disk Graph 3.0.3 Multilingual Free Links | macOS | 8 mb
Save disk space. Inspect your disk and find the files that occupy the most space or that haven’t been modified in a long time. Any directory reachable in the Finder can be opened. Use the context menu or keyboard shortcut to show selected files in the Finder or move them to the bin.

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Integrate Microsoft Graph in Your Applications


Free Download Integrate Microsoft Graph in Your Applications
Released 2/2024
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch
Skill Level: Intermediate | Genre: eLearning | Language: English + srt | Duration: | Size: MB
Are you ready to get up to speed with Microsoft Graph, the gateway to data and intelligence in Microsoft 365? Microsoft Graph provides a unified programmability model that you can use to access the tremendous amount of data in Microsoft 365, Windows, and Enterprise Mobility + Security. Not to mention, the Microsoft Graph API offers a single endpoint with access to rich, people-centric data and insights in the Microsoft cloud, allowing your custom applications to integrate with mail, calendar, contacts, documents, directory services, and more. In this course, join instructor Sahil Malik to learn how to integrate Microsoft Graph into your workflow with almost any conceivable application.

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Graph Coloring Problems


Free Download Graph Coloring Problems by Tommy R. Jensen, Bjarne Toft
English | PDF | 1994 | 313 Pages | ISBN : 0471028657 | 24.3 MB
Contains a wealth of information previously scattered in research journals, conference proceedings and technical reports. Identifies more than 200 unsolved problems. Every problem is stated in a self-contained, extremely accessible format, followed by comments on its history, related results and literature. The book will stimulate research and help avoid efforts on solving already settled problems. Each chapter concludes with a comprehensive list of references which will lead readers to original sources, important contributions and other surveys.

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Graph Algorithms for Data Science (MEAP V07)


Free Download Graph Algorithms for Data Science (MEAP V07)
English | 2023 | ISBN: 9781617299469 | 386 pages | MOBI | 6.09 Mb
Graph Algorithms for Data Science is a hands-on guide to working with graph-based data in applications like machine learning, fraud detection, and business data analysis. It’s filled with fascinating and fun projects, demonstrating the ins-and-outs of graphs. You’ll gain practical skills by analyzing Twitter, building graphs with NLP techniques, and much more. You don’t need any graph experience to start benefiting from this insightful guide. These powerful graph algorithms are explained in clear, jargon-free text and illustrations that makes them easy to apply to your own projects.

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Concepts and Techniques of Graph Neural Networks


Free Download Concepts and Techniques of Graph Neural Networks by Vinod Kumar, Dharmendra Singh Rajput
English | May 22, 2023 | ISBN: 1668469030 | 247 pages | MOBI | 8.93 Mb
Recent advancements in graph neural networks have expanded their capacities and expressive power. Furthermore, practical applications have begun to emerge in a variety of fields including recommendation systems, fake news detection, traffic prediction, molecular structure in chemistry, antibacterial discovery physics simulations, and more. As a result, a boom of research at the juncture of graph theory and deep learning has revolutionized many areas of research. However, while graph neural networks have drawn a lot of attention, they still face many challenges when it comes to applying them to other domains, from a conceptual understanding of methodologies to scalability and interpretability in a real system. Concepts and Techniques of Graph Neural Networks provides a stepwise discussion, an exhaustive literature review, detailed analysis and discussion, rigorous experimentation results, and application-oriented approaches that are demonstrated with respect to applications of graph neural networks. The book also develops the understanding of concepts and techniques of graph neural networks and establishes the familiarity of different real applications in various domains for graph neural networks. Covering key topics such as graph data, social networks, deep learning, and graph clustering, this premier reference source is ideal for industry professionals, researchers, scholars, academicians, practitioners, instructors, and students.

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