Journal of Business and Management Studies · 2024 · 11 citations · 12 references
ComputingBusiness AnalyticsComputer ScienceArtificial IntelligenceBusiness IntelligenceMachine LearningDeep LearningMachine Learning For Big DataNeural NetworksOrganizational StrategyRepresentation LearningBenchmark DatasetsBusiness Intelligence StrategyBusiness Intelligence SystemsConvolutional Neural NetworksDeep Learning For Big DataOrganizational Learning Processes
This research delves into the transformative impact of deep learning, specifically Convolutional Neural Networks (CNNs) such as VGG16, ResNet50, and InceptionV3, on organizational management and business intelligence. The study follows a comprehensive methodology, emphasizing the importance of high-quality datasets in leveraging deep learning for enhanced decision-making. Results demonstrate the superior performance of CNN models over traditional algorithms, with CNN (VGG16) achieving an accuracy rate of 89.45%. The findings underscore the potential of deep learning in extracting meaningful insights from complex data, offering a paradigm shift in optimizing various organizational processes. The article concludes by emphasizing the significance of investing in infrastructure and expertise for successful CNN integration, ensuring ethical considerations, and addressing data privacy concerns. This research contributes to the growing discourse on the application of deep learning in organizational management, providing a valuable resource for businesses navigating the dynamic landscape of the global market.
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