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We are going to be doing text classification using Spacy word embeddings in this video. I have taken a news data set where the news is classified as or real and this is a CSV file I have. Someone wrote a new saying top Trump surrogate brutally stabs in in the back. Clearly its a news and it is classified such in this CSV file. Lets load that file into pandas data frame. The data frame looks something like this if you notice the shape of the file 9900 records in total, and I will do value counts just to figure out if there is a class imbalance or not. Looks like none almost similar uh samples we have if these samples were very different lets say you have news is 5000 and real news is only 1000, then you have to do something to address that class imbalance. I will now convert this label column into numbers. Obviously machine learning models understand the numbers better than the text so from a label column I want to generate new column called label num which will be a