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

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. The software performs two primary functions; first, it determines the sentiment of the text (positive sentiment, negative sentiment, or neutral sentiment). Second, it extracts the top two 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 two extracted phrases by providing the context. It is important to keep in mind, that much of the analysis is dependent on the translation itself. This plays a part in the analysis as it is performed on the English translation. Except for a few Surahs, the translations are by Ahmed Ali, Amatul Rahman Omar, Daryabadi, Faridul Haque, Hamid S. Aziz, Maulana Mohammad Ali, Pickthall, Sarware, Shakir, and Yusuf Ali. The structure of each analysis is first the Surah (in English), then noted with the sentiment, then the top two phrase extraction, and then brief commentary of the extractions. The sentiment analysis is based on the entire Surah, and the top two extractions are what Machine Learning identifies are the most important or key identifications in the text, including being based on the context.