Project45 Data Science 프로젝트 (2주차 - 1) Data Preparation & Exploration Introduction This notebook aims at getting a good insight in the data for the PorteSeguro competition. Besides that, it gives some tips and tricks to prepare your data for modeling. The notebook consists of the following main sections: PorteSeguro 대회를 위한 데이터 통찰력 기르기 데이터 모델링을 위한 트릭과 팁들! Loading packages import pandas as pd import numpy as np import matplotlib.pyplot.. 2023. 3. 24. Data Science 프로젝트 (1주차 - 4) Introduction to Ensembling/Stacking in Python Introduction This notebook is a very basic and simple introductory primer to the method of ensembling (combining) base learning models, in particular the variant of ensembling known as Stacking. In a nutshell stacking uses as a first-level (base), the predictions of a few basic classifiers and then uses another model at the second-level to predict th.. 2023. 3. 18. Data Science 프로젝트 (1주차 - 3) Titanic Top 4% with ensemble modeling 1. Introduction Feature analysis Feature engineering Modeling import pandas as pd import numpy as np import matplotlib.pyplot as plt import seaborn as sns %matplotlib inline from collections import Counter from sklearn.ensemble import RandomForestClassifier, AdaBoostClassifier, GradientBoostingClassifier, ExtraTreesClassifier, VotingClassifier from sklearn.d.. 2023. 3. 18. Data Science 프로젝트 (1주차 - 2) EDA To Prediction (DieTanic) Sometimes life has a cruel sense of humor, giving you the thing you always wanted at the worst time possible. ## Part 1 : Exploratory Data Analysis(EDA) import numpy as np import pandas as pd import matplotlib.pyplot as plt import seaborn as sns plt.style.use('fivethirtyeight') import warnings warnings.filterwarnings('ignore') #경고 무시 %matplotlib inline #화면에 그래프 바로 출력.. 2023. 3. 18. 이전 1 ··· 8 9 10 11 12 다음
