FINAL TASK

     Today, I started what probably is my last work with Project Gutenberg. I am working on a named entity recognition. This is my second time applying timed entity recognition to this data. During my previous task, I used SpaCy to do the NER, but this time I am using JohnSnowLabs. JohnSnowLabs is a website with a collection of pre-trained machine learning pipelines. This time I am using the BERT pipeline to accomplish my task. The final result of my work will be a topic modeling and a named entity recognition which my supervisor will then analyze.

    I think it is the right time to reflect on some of the things I accomplished during these nine weeks of work. I have learned a lot from this experience, whether it is a way to complete work, a learning habit, or an ability to multitask, I have gained new skills, knowledge, and work experience. I believed that these gains will allow me to perform well in my future internship.

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FINAL POINT

       I recently completed my internship at Vanderbilt University, where I worked with an English professor and a librarian for a text-mining project. The goal of the project is to help the English professor in his research about how Law is represented in general dialogue during the Romanticism period (a period of literature between 1750 and 1850). So, the data collected were English books published in the United Kingdom and Ireland between 1770 and 1835. The main source of data was Project Gutenberg, an online library of free eBooks.       We faced a load of challenges while working on this project. One of the biggest issues was figuring out the correct book to collect. While project Gutenberg provides some information such as authors and editions of the book, it does not provide the year of publication, so there was no way for us to know what the right book is. We have attempted to solve the problem by collecting all the books in English and fr...
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