dhinesh25 Goto Github PK
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Dataset has been collected from fatkun chrome extension tool using that we can download bulk images and Used opencv for image pre processing. For feature engineering I have used wavelet transform which is used to extract important features from image. For model building , Logistic regression have been used. Since accuracy is not good Deep learning models like CNN can be used in future.
We used to classify whether a sentence is a hate speech or not a Hate speech, this classifier is built using BERT model. We have pre-Processed training sentences by taking the emojis out and replacing it with the real emotions in text. We are taken out the stop words, and We cleared the HTML tags, Mentions, Hashtags
Mall Customer Segmentation using KMeans.
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