Verses of the Quran Analyzed with Machine Learning using Natural Language Processing - Softcover

Qureshi, Faisal Ahmad

Softcover

ISBN 13: 9798642222294

Publisher: Independently published, 2020

Synopsis

This book is about the results of analyzing the Quran with Machine Learning using Natural Language Processing (NLP). This was performed using software developed by Hourglass Software LLC and leverages Amazon AWS Comprehend service (NLP). Not all Surahs are analyzed, however. Thus, the entire of the Quran is not covered, but we can see the results of analysis of the ones that are. It extracts the top few key phrases of the text (based on Machine Learning confidence score). You will see that each Surah analyzed will show these results. Additionally, there is brief commentary of the top extracted phrases by providing the context. The analysis is done on the original Arabic text and two translations in English. The first translation is done by different people (different translators for different Surahs) who are Ahmed Ali, Amatul Rahman Omar, Daryabadi, Faridul Haque, Hamid S. Aziz, Maulana Mohammad Ali, Pickthall, Sarware, Shakir, and Yusuf Ali. This is published on the Quran 411 website. The second translation is for “Clear Quran” done by Talal Itani. The structure of each analysis is first the Surah in Arabic, then the English translations and then details of the analysis. The top extractions are the exact word/s in Arabic, then the English corresponding translation. The top extractions are what Machine Learning identifies are the most important or key identifications in the text, including being based on the context and other algorithms used by Natural Language Processing. Furthermore, the Surahs are not in any order. It also has counts of the number of Ayats that the selected words by NLP exist in in the entire Quran. If I have mentioned anything incorrect in the short comments, may Allah Almighty forgive me for only Allah knows best.

Edition details

• Publisher: Independently published
• Publication date: 2020
• Language: English
• ISBN 13: 9798642222294
• Binding: Paperback
• Number of pages: 229