/CSAT_Vocab

Pi_ville_project

Primary LanguagePython

CSAT_Vocab

Pi_ville_project

KakaoTalk_20190701_205943204

KakaoTalk_20190701_205946567

KakaoTalk_20190701_205948916

KakaoTalk_20190701_205951959

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Introduction

We are planning to make 2020 CSAT by using deep learning. Especially for English, we are going to realize the model for 6 types of R/C and 6 types of L/c in order to produce nearly same quality of CSAT. Based on deep learning, we are using TENSORFLOW and KERAS package and make the dictionary for vocabulary used in CSAT and the passage dataset by using Word2Vec and Embedding technique. We lay out using RNN (Recurrent Neural Networks), escpecially (LSTM) Long Short-Term Memory model in order to make passages which would be used to make CSAT made by deep learning.