Job&Interview.md

###面试准备###

1. SQL
2. Machine Learning算法
3. NLP算法
4. Coding
5. 简历知识点

###Springleaf

######Categorical features

1. High cardinality features(leave-one-out encoding)

2. parameter tuning(XGBoost)

   • learning rates vs. number of rounds
   • max depth vs min child weight (Tree-based parameters)
   • Boosting parameters(row sample, column sample)

3. High correlated features

   • removed for linear models
   • tree-based models(leave out for the models)

4. Dates, Time-Series

5. What is the difference between categorical, ordinal and interval variables?

6. kaggle Ensemble Guide

7. Tips for data science competitions

###Job Interview

1. 解读IT面试黑科技
2. 面试升级之路 (一拳超人)
3. 刷题

• 走出刷题的误区
• 面试知识点梳理

4. 小土刀的面试刷题笔记
5. Linkedin好友数12000+有什么奇妙的体验？ H1B visa Database