Learn the importance of data analytics in fraud management and how it can streamline risk assessment, prevention, detection, audit planning, and investigation processes. Discover key areas where data analytics can make a difference and avoid common mistakes in your fraud analytics plan. Embrace data

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\"Fixity EDX offers top-notch upskilling opportunities for students and professionals with data analyst, skill development, and corporate training programs. Gain high-quality skills and industry-recognized certification for enhanced career prospects.\" \n\nAre you intrigued by the vast potential of

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Explore the evolution of Machine Learning in Graphs, from traditional ML tasks to advanced Graph Neural Networks (GNNs). Discover key concepts like feature engineering, tools like PyG, and types of ML tasks in graphs. Uncover insights into node-level, graph-level, and community-level predictions, an

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Delve into the world of data analytics through this comprehensive guide covering topics such as the definition of data, big data, analytics vs analysis, the importance of data analytics, real-world applications, and more. Explore the classification of data, the 3Vs of big data, and how data analytic

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In the end Vinz Global's dedication to using climate data analytics to build sustainable supply chains illustrates its ability to lead positive change and generating benefits for society and the environment. Through integrating climate data analytics into its business operations, Vinz Global gains i

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This paper introduces the Localised Adaptive Spatial-Temporal Graph Neural Network model, focusing on the importance of spatial-temporal data modeling in graph structures. The challenges of balancing spatial and temporal dependencies for accurate inference are addressed, along with the use of distri

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Graph Neural Networks (GNNs) are a versatile form of neural networks that encompass various network architectures like NNs, CNNs, and RNNs, as well as unsupervised learning models such as RBM and DBNs. They find applications in diverse fields such as object detection, machine translation, and drug d

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This comprehensive presentation delves into the fundamentals of Neo4j graph database, covering topics such as the definition of graph databases, reasons for their usage, insights into Neo4j and Cypher, practical applications like data flow analysis, and hands-on instructions on creating and querying

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Cloud Analytics Market Size, Share, Forecast, & Trends Analysis by Offering (Solutions, Services), Type (Predictive Analytics, Diagnostic Analytics, Prescriptive Analytics), Deployment Mode, Sector (BFSI, Retail & E-commerce, Healthcare & Life Sciences), and Geography - Global Forecast to 2031\n

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Discover why your current business analytics tool may no longer meet the demands of today's data-driven landscape. This blog explores the limitations of outdated analytics platforms and guides you through the essential features of next-generation tools that can enhance your decision-making capabilit

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This content delves into the Breadth-First Search (BFS) algorithm, a fundamental graph searching technique. It explains the step-by-step process of BFS, from initializing the graph to traversing vertices in a specific order. Through detailed visual representations, you will gain insights into how BF

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Graph-based data science offers a powerful approach to analyzing data by leveraging graph structures. This involves using graph representation, analysis algorithms, ML/AI techniques, kernels, embeddings, and neural networks. Real-world examples show the utility of data graphs in various domains like

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Explore the intriguing concepts of the Friendship Theorem and Freshman's Dream in graph theory along with examples and visual illustrations. Learn about common friends, relationships between vertices and edges, and what defines a graph in a concise yet comprehensive manner.

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In this workshop, distinguished panelists including Ananth Iyer, Apurva Jain, Subodha Kumar, and Yao Zhao share insights and expertise on supply chain analytics. Topics include program introductions, audience engagement, format, content criteria, and analytics applications. Participants will gain va

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Graph Theory Matchings have a rich history dating back to the 9th century AD. Distinct Representatives and Hall's Theorem play important roles in determining matchings in graphs. Understanding concepts like bipartite graphs, maximum matchings, and Hall's Marriage Theorem is essential in graph theory

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This research examines how the use of data analytics and consulting activities affect perceived internal audit quality. The study investigates the relationship between these factors and top management's perception of internal audit quality. Through online scenario-based experiments with middle and t

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Data bias can distort your analytics and lead to misguided decisions. In this blog, learn how to identify common signs of data bias, understand its impacts, and explore effective strategies to correct it. Enhance the accuracy and reliability of your insights with practical tips and advanced tools, e

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Freebase was initially created in 2005 as an open shared database of knowledge, later acquired by Google and absorbed into the Google Knowledge Graph. Its approach included crowdsourcing updates and additions, focusing on data rather than text. The schema of Freebase included around 1500 types, 3500

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In this lecture, Kasey Champion covers a wide range of topics including graph algorithms, data structures, coding projects, and important midterm topics for CSE 373. The lecture emphasizes understanding ADTs, data structures, asymptotic analysis, sorting algorithms, memory management, P vs. NP, heap

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Uncover the power of Microsoft Graph through accessing files, extending Microsoft 365 experiences, and utilizing the gateway to Microsoft Cloud data. Learn about authentication options and how to interact with the Microsoft Graph Direct REST API.

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Delve into the realm of Deep Graph Theory where graph theory statements are analyzed beyond their conventional scope to uncover philosophical insights and correct misunderstandings. Discover the essence of trees, forests, and the unique relationship where every tree is regarded as a forest. Addition

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Freebase was launched in 2005 as an open database of knowledge, initially populated with Wikipedia data and later incorporating crowdsourced updates. Acquired by Google in 2010, it was transitioned into Google's Knowledge Graph before being decommissioned in 2016. The schema contained around 1500 ty

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Businesses are leveraging data and analytics capabilities to transform decision-making processes. This shift has been driven by the availability of vast amounts of data, improved computational power, and sophisticated algorithms. The incorporation of business analytics in various sectors like market

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Delve into the basics of graph theory with topics like graph embeddings, graph plotting, Kuratowski's theorem, planar graphs, Euler characteristic, trees, and more. Explore the principles behind graphs, their properties, and key theorems that define their structure and connectivity.

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Learn how to identify different graph shapes such as symmetric, skewed, and uniform, and understand descriptors like unimodal and bimodal. Explore practical examples and visual aids to enhance your graph interpretation skills.

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Dive into the world of association rules with graph patterns, where relationships and connections are analyzed through nodes and edges. Discover how to define association rules, identify customers, and uncover interesting patterns using graph-based techniques. Explore traditional and graph-pattern a

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Investigating natural language interfaces for querying structured MOF data stored in a knowledge graph, this project focuses on developing strategies using NLP to translate NL questions to KG queries. The MOF-KG integrates datasets, enabling query, computation, and reasoning for deriving new knowled

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An intriguing mathematical problem is presented where new faculty members at TIMS must be assigned to coffee lounge alcoves in a way that ensures no two new members meet after the first day. By constructing a graph based on meet-up timings, analyzing clashes, and determining intervals, this scenario

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The content discusses the concepts of graph connectivity and single element recovery using linear and OR queries. It delves into the strategies, algorithms, and tradeoffs involved in determining unknown vectors, edges incident to vertices, and spanning forests in graphs. The talk contrasts determini

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In this study by Uriel Feige and Roee David from the Weizmann Institute, the effect of randomness on planted 3-coloring models is investigated. The research delves into the NP-hard nature of 3-coloring problems, introducing a hosted coloring framework that involves choices like the host graph and th

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Discover how predictive analytics is transforming the mobile app development landscape in our latest blog, How Predictive Analytics is Shaping the Future of Mobile App Development. By leveraging data and machine learning models, predictive analytics

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This research discusses the challenges in managing large graphs on multi-core systems and introduces Grace, an in-memory graph management and processing system with optimizations for graph-specific and multi-core-specific operations. The system keeps the entire graph in memory in smaller parts and p

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This class introduces the fundamentals of distributed graph algorithms focusing on network modeling, complexity measures, solving graph problems, and comparing distributed vs. centralized algorithms. It covers topics such as the LOCAL model, synchronous rounds, communication rounds, computation time

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Delve into the fascinating world of graph colorings, chromatic polynomials, and notable conjectures in discrete geometry. Explore the impact of June Huh in bringing Hodge theory to combinatorics and his proof of various mathematical conjectures. Uncover the significance of the four-color theorem, co

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This research introduces a groundbreaking distributed memory multi-GPU graph coloring implementation, achieving significant speedups and minimal color increase. The approach enables efficient coloring of large-scale graphs with billions of vertices and edges. Additionally, the study explores the pra

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Maria's bike journey graph depicts her distance from home as she rode to meet friends and run errands before returning home. The graph shows her stops for errands, changes in direction, and her path back home. By interpreting the key features of the graph, such as intercepts and intervals, we can an

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The content discusses the concept of maximal independent sets in graph theory. It defines independent, maximal, and maximum sets, highlighting the difficulty in finding a maximum independent set due to its NP-hard nature. Sequential and parallel algorithms for finding maximal independent sets are pr

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Balanced graph edge partitioning is a crucial problem in graph computation, machine learning, and graph databases. It involves partitioning a graph's vertices or edges into balanced components while minimizing cut costs. This process is essential for various real-world applications such as iterative

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Explore the concept of spanning trees and minimum spanning trees in graph theory through an in-depth lecture outline covering topics like Cut Property, Cycle Property, Kruskal's Algorithm, and more. Delve into the significance of Minimum Spanning Trees (MSTs) as the lowest-cost spanning tree of a gr

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This content explores the design requirements, state-of-the-art technologies, trade-offs, goals, and approach for achieving efficient incremental processing in stream analytics. It emphasizes the need to balance advantages of batch-based systems with the efficiency of incremental updates for sliding

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