<\/p>\n
Author<\/strong>: Shashwat Sharma \u00a0<\/p>\n Artificial Neural Networks (ANN) are a subset of machine learning inspired by the structure and function of biological neural networks in the human brain. ANNs have gained widespread adoption in areas such as image recognition, speech processing, and financial modeling due to their ability to identify patterns and make predictions. This research explores the history, architecture, learning mechanisms, applications, challenges, and future prospects of ANNs.<\/p>\n \u00a0<\/p>\n Artificial Neural Networks (ANNs) are computing models that attempt to simulate the way the human brain processes information. They consist of interconnected nodes (neurons) that process data and learn from experience. The growing computational power and availability of large datasets have propelled ANN into a central role in artificial intelligence (AI).<\/p>\n The primary objective of this research is to explore the theoretical foundation, applications, and challenges associated with ANN, as well as the future scope of this technology.<\/p>\n <\/span>\u00a0<\/span>SHAPE \u00a0<\/span>* MERGEFORMAT <\/span><\/p>\n <\/p>\n <\/span><\/p>\n The foundation of ANNs was laid by McCulloch and Pitts (1943), who proposed the first mathematical model of a neuron. Later, Rosenblatt (1958) introduced the perceptron, which was one of the first machine learning models capable of performing classification tasks. The backpropagation algorithm, developed in the 1980s by Rumelhart, Hinton, and Williams (1986), significantly improved the training of multi-layer networks, leading to the rise of deep learning.<\/p>\n In recent years, architectures such as Convolutional Neural Networks (CNNs) (LeCun et al., 1998) and Recurrent Neural Networks (RNNs) (Hochreiter & Schmidhuber, 1997) have revolutionized fields like image recognition and natural language processing. Transformer models, such as BERT (Devlin et al., 2018) and GPT (Brown et al., 2020), have further pushed the boundaries of ANN applications in language understanding.<\/p>\n This study is based on secondary research, including a review of peer-reviewed journal articles, conference papers, and books. The research focuses on identifying key principles of ANN, their applications, and the challenges in implementation.<\/p>\n Artificial Neural Networks typically consist of three main layers:<\/p>\n Each neuron in these layers is connected by weights that adjust during the learning process. The number of hidden layers determines the depth of the network.<\/p>\n ANNs learn from data through various training methods:<\/p>\n Despite their success, ANNs face several challenges:<\/p>\n Artificial Neural Networks have transformed multiple fields, offering powerful solutions for complex problems. However, challenges like high computational requirements and lack of interpretability still need to be addressed. Future research should focus on developing more efficient ANN architectures, improving explainability, and ensuring ethical AI development.<\/p>\n <\/p>\n","protected":false},"excerpt":{"rendered":" Author: Shashwat SharmaRoll No: 120Institution: Kohinoor Business School \u00a0 Abstract Artificial Neural Networks (ANN) are a subset of machine learning inspired by the structure and function of biological neural networks in the human brain. ANNs have gained widespread adoption in areas such as image recognition, speech processing, and financial modeling due to their ability to… Continue reading Artificial Neural Network<\/span><\/a><\/p>\n","protected":false},"author":139829,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-22419","post","type-post","status-publish","format-standard","hentry","category-uncategorized","entry"],"_links":{"self":[{"href":"http:\/\/www.sachdevajk.in\/index.php?rest_route=\/wp\/v2\/posts\/22419","targetHints":{"allow":["GET"]}}],"collection":[{"href":"http:\/\/www.sachdevajk.in\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"http:\/\/www.sachdevajk.in\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"http:\/\/www.sachdevajk.in\/index.php?rest_route=\/wp\/v2\/users\/139829"}],"replies":[{"embeddable":true,"href":"http:\/\/www.sachdevajk.in\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=22419"}],"version-history":[{"count":1,"href":"http:\/\/www.sachdevajk.in\/index.php?rest_route=\/wp\/v2\/posts\/22419\/revisions"}],"predecessor-version":[{"id":22420,"href":"http:\/\/www.sachdevajk.in\/index.php?rest_route=\/wp\/v2\/posts\/22419\/revisions\/22420"}],"wp:attachment":[{"href":"http:\/\/www.sachdevajk.in\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=22419"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/www.sachdevajk.in\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=22419"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/www.sachdevajk.in\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=22419"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
Roll No<\/strong>: 120
Institution<\/strong>: Kohinoor Business School<\/p>\nAbstract<\/span><\/strong><\/h2>\n
Introduction<\/span><\/strong><\/h2>\n
Literature Review<\/span><\/strong><\/h2>\n
Historical Background<\/span><\/strong><\/h3>\n
Recent Developments<\/span><\/strong><\/h3>\n
Research Methodology<\/span><\/strong><\/h2>\n
Findings and Discussion<\/span><\/strong><\/h2>\n
1. Architecture of ANN<\/span><\/strong><\/h3>\n
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2. Learning Mechanisms<\/span><\/strong><\/h3>\n
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3. Applications of ANN<\/span><\/strong><\/h3>\n
Healthcare<\/span><\/strong><\/h4>\n
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Finance<\/span><\/strong><\/h4>\n
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Automotive<\/span><\/strong><\/h4>\n
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Marketing<\/span><\/strong><\/h4>\n
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4. Challenges in ANN<\/span><\/strong><\/h3>\n
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Conclusion<\/span><\/strong><\/h2>\n
References<\/span><\/strong><\/h2>\n
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