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[sklearn, NLP] 상품 리뷰 분석 NLP, Count Vectorizer, Naive Bayes Classifier

NLP 상품 리뷰 분석¶ In [2]: import pandas as pd import numpy as np import matplotlib.pyplot as plt import seaborn as sns In [3]: data = pd.read_csv('./09. 상품 리뷰 분석(NLP)/yelp.csv', index_col =0) In [4]: data.head() Out[4]: review_id user_id business_id stars date text useful funny cool 2967245 aMleVK0lQcOSNCs56_gSbg miHaLnLanDKfZqZHet0uWw Xp_cWXY5rxDLkX-wqUg-iQ 5 2015-09-30 LOVE the cheeses here. They ..
Machine Learning, Deep Learning 2021. 1. 24. 00:09
[sklearn] Logistic Regression을 활용한 소비자 광고 반응률 예측

Logistic Regression을 활용한 소비자 광고 반응률 예측¶ In [1]: import pandas as pd import numpy as np import matplotlib.pyplot as plt import seaborn as sns In [3]: df = pd.read_csv('./03. 광고 반응률 예측 (Logistic Regression)/advertising.csv') df.head(10) Out[3]: Daily Time Spent on Site Age Area Income Daily Internet Usage Ad Topic Line City Male Country Timestamp Clicked on Ad 0 68.95 NaN 61833.90 256.09 Cloned 5t..
Machine Learning, Deep Learning 2021. 1. 22. 23:10
[sklearn,statsmodels] Linear Regression을 이용한 고객별 연간 지출액 예측

02 Linear Regression을 이용한 고객별 연간 지출액 예측(statsmodels 사용)¶ In [1]: import pandas as pd import numpy as np import matplotlib.pyplot as plt import seaborn as sns In [2]: data = pd.read_csv('./02 Linear Regression을 이용한 고객별 연간 지출액 예측/ecommerce.csv') In [3]: data.head() Out[3]: Email Address Avatar Avg. Session Length Time on App Time on Website Length of Membership Yearly Amount Spent 0 mstephenson@fe..
Machine Learning, Deep Learning 2021. 1. 22. 23:03
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