ANNUITY_INCOME_PERCENT: 贷款年金和收入比the percentage of the loan annuity relative to a client's income CREDIT_TERM: 连续还款月长度 the length of the payment in months (since the annuity is the monthly amount due DAYS_EMPLOYED_PERCENT: 受雇佣天数与年龄比the percentage of the days employed re...
In the next post, you'll take the time to build some Machine Learning models, based on what you've learnt from your EDA here. We'll do this in the next post on this project (to be launched on December 27). Temas Python Data Science Data Analysis Machine Learning Hugo Bowne-AndersonDa...
Kaggle金牌得主的Python数据挖掘框架,机器学习基本流程都讲清楚了 编程算法python机器学习决策树神经网络 导语:很多同学在学习机器学习时往往掉进了不停看书、刷视频的,但缺少实际项目训练的坑,有时想去练习却又找不到一个足够完整的教程,本项目翻译自kaggle入门项目Titanic金牌获得者的Kernel,该篇文章通过大家并不陌生的...
Aggregate the global primary energy consumption by year, then build an autoregressive integrated moving average (ARIMA) model to project total global energy consumption for the next few years. Plot the historical and forecasted energy consumption using Matplotlib.Python 複製 ...
Project for restoring beautiful K-pop Idols Images to high quality. Python135 JobCare--DACONJobCare--DACONPublic 데이콘 직업 추천 알고리즘 경진대회 Jupyter Notebook1 kaggle_cv_course_koreankaggle_cv_course_koreanPublic ...
# Dump the datasourcing, features engineered and the variables tracked in a xlsx file V.dump(techniqueUsed='XGBoost',filename="vevestaDump1.xlsx",message="XGboost with data augmentation was used",version=1, repoName='My_Project') Alternatively, write the experiment into the default file, ve...
Aggregate the global primary energy consumption by year, then build an autoregressive integrated moving average (ARIMA) model to project total global energy consumption for the next few years. Plot the historical and forecasted energy consumption using Matplotlib.Python Kopeeri ...
Explore and run machine learning code with Kaggle Notebooks | Using data from No attached data sources
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We will now explore how to perform Automated EDA using the analyze and compare methods in sweetviz. Getting ready We will work with the Customer Personality Analysis data from Kaggle on this recipe. You can retrieve all the files from the GitHub repository. How to do it… We will learn...