I'm quite new to Deep Learning and trying to solve the problem of Multi-Class, multi-label text classification using Deep Learning.
https://github.com/fchollet/keras/blob/master/examples/imdb_cnn_lstm.py . I've another dataset. int form of a csv file ("text","classifier"), on which i want to perform text classification task. I've tried a few ways to pass my training text to keras but couldn't so I'm stuck at this point. Can anyone suggest me how should I pass my "train.csv" and "test.csv" file to the X_train, y_train and X_test, y_test?
Typically stuck in this line.
(X_train, y_train), (X_test, y_test) = imdb.load_data(nb_words=max_features)
'train.csv' has this format:
"Job Description:An ideal fitment would apply his/ her advanced analytics expertise at a cutting edge Industrial Analytics specialized Data Science organization; primarily, in any of the following areas- automotive/ energy/ oil & gas/ aerospace/ marine/ chemical. Experience in statistical modeling, predictive modeling, Random forests, Decision tree, Linear Regression, Correlation, Time- series. BE / MS/ PhD in Mechanical/ OR/ IE/ computer science/ EE/ chemical. Mentor/ Lead a small team of data scientist",Business Analytics
'test.csv' has same format that is "job_description","category"