[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-118859-en":3,"doc-seo-118859-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},118859,8796095360427,"Lucas Martin","https://ap-avatar.wpscdn.com/davatar_994ba38a5ba835b3df7d355c54d3ed8d",8,"Research & Report","An Evaluation of Machine Learning and Big Data Analytics Performance in Cloud Computing and Computer Vision - Research","Although cloud computing is widely adopted, security concerns remain a major barrier to broader use, especially around data loss, security risks, and availability. With the surge of sensor- and web-generated data, applications have shifted toward machine learning, where Big Data and cloud services are key themes in IT. This review evaluates Big Data analytics and machine learning ideal models for cloud computing and computer vision, focusing on automated analysis of large datasets, model generation for data relationships, and comparison of ML-based threat detection approaches.","An Evaluation of Machine Learning and Big Data Analytics Performance in Cloud Computing and  \nComputer Vision  \nHather Ibraheem Abed1, Nawar A. Sultan2, Osama Yassin Mohammed3  \n1Northern Technical University, Iraq  \n[Email: hadiria@ntu.edu.iq](Email: hadiria@ntu.edu.iq)  \n2Northern Technical University, Iraq  \nEmail: [nawarabd@ntu.edu.iq](nawarabd@ntu.edu.iq)  \n3Northern Technical University, Iraq  \nEmail: [osama.yassin@ntu.edu.iq](osama.yassin@ntu.edu.iq)  \nAbstract: Although cloud computing is receiving a lot of attention, security remains a significant barrier to its general adoption. Cloud service users frequently worry about data loss, security risks, and availability issues. Because of the accessibility and openness of the huge volume of data amassed by sensors and the web throughout recent years, computer applications have seen a remarkable change from straightforward data processing to machine learning. Two widely used technologies, Big Data and Cloud computing, are the focus of worry in the IT industry. Enormous data sets are put away, handled, and broke down under the possibility of \"Big Data.\" Then again, cloud computing centres around giving the framework to make such systems conceivable in a period and cash saving way. The objective of the review is to survey the Big Data Analytics and Machine learning ideal models for use in cloud computing and computer vision. The programmed data examination of enormous data sets and the production of models for the wide connections between data are the centre highlights of machine learning (ML) . The usefulness of machine learning-based strategies for identifying threats in a cloud computing environment is surveyed and compared in this research.  \nKeywords: Machine learning, Artificial intelligence, Big data analytics, Cloud computing, Computer vision.  \nI. INTRODUCTION  \nThe use of cloud computing has grown in popularity recently. The customised data centres have gained popularity as a lowcost infrastructure option for corporate strategies. Internet services are just one of the many resources that cloud computing provides. Cloud computing offers a variety of online resources that help individuals and organisations cut infrastructure costs. End users continue to utilise and distribute infrastructure as a service (IaaS), platform as a service (PaaS), and software as a service (SaaS) in large numbers. In this approach, customers can deploy their apps without needing to maintain or control the infrastructure for cloud computing or have any understanding of it. Instead, they merely use hardware or software that they access or rent and only pay for what they really use. The option to pay as you go, which is highly sought by cloud hosting providers, is becoming more and more common in the corporate computing paradigm (KOBIELUS, 2018) .  \nThe driving factor behind all of the earth's sciences will be big data. Massive amounts of data are being produced by the digital empire (in Zetta Bytes now) . All areas of science, particularly astronomy and medical research, primarily rely  \non data collected from a variety of sources. In the current technological environment, producing data is not a problem, but processing, storing, and retrieving it is a major challenge. The issue of learning, analytics, and prediction from such avast volume of data is even more serious. But thanks to cloud computing, the scenario for big data analysis and storage is no longer as difficult to complete as it once was.  \nThe objective of machine learning and computer vision is to enable computers to detect data, appreciate data, and make moves in light of past and present results. Computer vision and machine learning research are still being developed. The Web of Things, Modern Web of Things, and cerebrum human points of interaction all rely upon computer vision. Utilizing machine learning and computer vision, the complicated human ways of behaving in media streams are distinguished and monitored. There are variou","cbCaii4WbVwwJFOX","https://ap.wps.com/l/cbCaii4WbVwwJFOX","pdf",503671,1,10,"English","en",105,"# Introduction\n## Background of the study","[{\"question\":\"What security issues hinder the adoption of cloud computing?\",\"answer\":\"Security concerns include worries about data loss, security risks, and availability issues that affect general adoption.\"},{\"question\":\"How does the document connect Big Data with cloud computing and machine learning?\",\"answer\":\"It describes Big Data as large datasets that are stored, processed, and analyzed, while cloud computing provides the infrastructure needed to enable such systems in a cost-effective way.\"},{\"question\":\"What is the main objective of the review regarding ML and computer vision?\",\"answer\":\"The review aims to evaluate Big Data analytics and machine learning models for use in cloud computing and computer vision, with emphasis on automated analysis and ML-based threat identification.\"}]","An Evaluation of Machine Learning and Big Data Analytics Performance in Cloud Computing and Computer Vision - 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