Titlebook: Indian Multinationals; The Dynamics of Expl Amar K. J. R. Nayak Book 2011 Palgrave Macmillan, a division of Macmillan Publishers Limited 20

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Amar K. J. R. Nayakfound in legal documents. Traditionally, this challenge has been approached as a single-class text classification problem. However, due to the inherent complexity of legal information, characterized by intricate connections and associations between various legal entities and concepts, we propose tha

Palter

Amar K. J. R. Nayakmation retrieval and data collection for machine learning, research, and survey reports in various fields such as meteorology, science, geography, literature, and more. However, manual data collection and classification can be time-consuming and prone to errors. Additionally, AI assistants used for

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Amar K. J. R. Nayake sophisticated synthetic media created using deep learning techniques that alter or replace visual and audio elements in images, videos, and audio recordings. While Deepfakes offer potential benefits in entertainment and training, they also raise ethical, social, and security concerns. Many people

arrhythmic

Amar K. J. R. Nayakondemning this jaundiced attitude. Ironically, however, the dialogue on both sides is filled with offensive and abusive language. While abusive language directed at Asians encourages violence and hate crimes against this ethnic group, the use of derogatory language to insult alternative points of vi

arbovirus

Amar K. J. R. Nayakinfections in Austria (particularly in Vienna). We focus on predicting users’ protest activity by leveraging machine learning methods and individual driving factors such as language features of users supporting/opposing Corona protests. For evaluation of our methods we utilize novel datasets, collec

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