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NLP & Python Exercise

PTA & Daily exercise

#1_jsonsort
Using json packet to decode json files and do some basic statistics.

#2_cos distance
Using Gensim and pre-trained word2vec model (GoogleNews-vectors-negative300.bin) to calculate the cosine distance between the vectors.

#3_passage cos distance
Using Gensim and pre-trained word2vec model (GoogleNews-vectors-negative300.bin) to calculate the cosine distance between two passages.
Also, with the help of Alir3z4/stop-words to do data pre-processing (Link: https://github.com/Alir3z4/stop-words).

#4_MLPtrain with packaged dataset
Using sklearn to train a MLPClassifer based on neural network with original packaged datasets.

#5_MLPtrain with own dataset
Using sklearn to train a MLPClassifer based on neural network with my own datasets.

#6_MLP predict
Using trained MLPClassifer to predict model & calculate the value of accuracy of the test category and predicted category.