Shashank sohamshashank1

Data Scientist

sohamshashank1 / loadModel.py

Created April 3, 2018 03:45 — forked from vgpena/loadModel.py

Basic text classification with Keras and TensorFlow

	import json
	import numpy as np
	import keras
	import keras.preprocessing.text as kpt
	from keras.preprocessing.text import Tokenizer
	from keras.models import model_from_json

	# we're still going to use a Tokenizer here, but we don't need to fit it
	tokenizer = Tokenizer(num_words=3000)
	# for human-friendly printing

sohamshashank1 / gist:2d0f6e495acc5da587917a679e56841d

Last active March 29, 2018 17:51

Text Classification with RNN

	## Objective to to classify text/ sentences using RNN
	## IMDB dataset is considered which contains 25,000 highly-polar movie reviews (good or bad) for training and the same amount again for testing. The problem is to determine whether a given movie review has a positive or negative sentiment.

	```
	# LSTM for sequence classification in the IMDB dataset
	import numpy
	from keras.datasets import imdb
	from keras.models import Sequential
	from keras.layers import Dense
	from keras.layers import LSTM