Bsc.CSIT final project report is the 7th sem project report especially working on NLP (Natural Language Processing). In computer science from Tribhuvan university, you need to apply a machine-learning algorithm to your final project. This project is all about how to classify
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In this blogging series, we discussed different approaches and concepts of sentiment analysis of Nepali sentences. Preprocessing, Vectorization is an important part. In this article, we make a model using siket learn. Naive Bayes algorithm is used, to Sentiment Analysis of Nepali
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Sentiment Analysis of Nepali Sentences | TFIDF in this article we are converting our sentences into vectors. TF, IDF, and TFIDF overall is vectorization technique in NLP(Natural Language Processing). TF(Term Frequency) In Sentiment Analysis of Nepali Sentences | TFIDF TF is first
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Vectorization is the process of converting categorical data into numerical form. Sentiment analysis is all about categorical / sentence-level analysis. It is must important part of sentiment analysis of Nepali sentences as well as other languages. In this article, we further discussed
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In this article, we discussed data collection and some preprocessing. Data collection for this project was done manually from different websites and Facebook groups.