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Sanskar
Keen Learner and Exp... • 10h
Day 9 of learning AI/ML as a beginner. Topic: Bag of Words practical. Yesterday I shared the theory about bag of words and now I am sharing about the practical I did I know there's still a lot to learn and I am not very much satisfied with the topic yet however I would like to share my progress. I first created a file and stored various types of ham and spam messages in it along with the label. I then imported pandas and used pandas.read_csv funtion to create a table categorizing label and message. I then started cleaning and preprocessing the text I used porter stemmer for stemming however quickly realised that it is less accurate and therefore I used lemmatization which was slow but gave me accurate results. I then imported countvectorizer from sklearn and used it to create a bag of words model and then used fit_transform to convert the documents in corplus into an array of 0 and 1 (I used normal BOW though). Here's what my code looks like and I would appreciate your suggestions and recommendations.
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