A Systematic Review Of Artificial Intelligence Based Methods In This paper presents a comprehensive review of artificial intelligence (ai) and machine learning (ml), exploring foundational concepts, emerging trends, and diverse applications. Some of the critical topics in deep learning, namely, transfer, federated, and online learning models, are explored and discussed in detail. finally, challenges and future directions are outlined to provide wider outlooks for future researchers.
Deep Learning Pdf Deep Learning Artificial Neural Network It traces the development of ai from early symbolic systems to modern machine learning and deep learning technologies, highlighting different ai types such as narrow ai, general ai, and the speculative concept of superintelligence. Artificial intelligence (ai) has become a core component of modern computer science, driving innovation across diverse application domains. this systematic review examines emerging applications of artificial intelligence in computer science by synthesizing recent scholarly literature. This comprehensive review examines the current state of artificial intelligence research, analyzing key developments in machine learning, deep learning, natural language processing, and computer vision. The aim of this study is to synthesize existing literature in order to classify and identify an appropriate deep learning method for a given task. a systematic literature review was conducted as a comprehensive method of study, utilizing literature spanning from 2012 to 2024.
Pdf A Systematic Review Do The Use Of Machine Learning Deep This comprehensive review examines the current state of artificial intelligence research, analyzing key developments in machine learning, deep learning, natural language processing, and computer vision. The aim of this study is to synthesize existing literature in order to classify and identify an appropriate deep learning method for a given task. a systematic literature review was conducted as a comprehensive method of study, utilizing literature spanning from 2012 to 2024. The results of this study showed that machine learning and deep learning are two distinct branches of artificial intelligence. machine learning is used for tasks such as image recognition, natural language processing, and predictive modeling. In this study, we use learning analytics (la) in higher education as a case context to examine how machine learning can improve the review process. This paper explores the maximum aspects focused on deep learning, including some of the latest architectures and technologies, how deep learning methodologies work as well as their real world applications. Therefore, motivated by the limitations, this study aims to comprehensively review the state of the art deep learning models in computer vision, natural language processing, time series analysis and pervasive computing, and robotics.
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