Get the free Comparative analysis of deep learning based Afaan Oromo hate speech detection. Journ...
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(2022) 9:76
Gunfire Journal of Big Data
https://doi.org/10.1186/s4053702200628wRESEARCHOpen AccessComparative analysis of deep learning based
Again Promo hate speech detection
Kaddish Omani Gunfire**Correspondence:
gaddisaolex@gmail.com
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What is comparative analysis of deep?
Comparative analysis of deep refers to the systematic review and evaluation of deep learning models and techniques in order to assess their performance, strengths, and weaknesses in various applications.
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Entities involved in deep learning research, development, or deployment may be required to file comparative analyses to comply with regulatory standards or organizational policies.
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To fill out a comparative analysis of deep, one should gather relevant data on deep learning models, define evaluation metrics, conduct experiments or analyses, and document the findings in a structured manner.
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The purpose of comparative analysis of deep is to enable stakeholders to make informed decisions by providing insights into the effectiveness, efficiency, and suitability of different deep learning approaches.
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The report should include model descriptions, performance metrics, comparative results, methodology used, limitations, and any recommendations based on the analysis.
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