1. Machine learning 知识点
模型假设
模型梗概
K-means
Decision Trees
Random Forest
GBDT
Neural Network
SVM
Classification & Regression
模型metric
overfitting
imbalance dataset
variance-bias trade-off
2. A/B test
3. 统计知识
central limit theory
几个重要不等式
复习statistical inference
p-value
regression
overdispersion
Deviance
etc
4. 简历(Situation, Target, Action, Result)
1. Global scholars program
2. DBA
3. The wandering Earth
4. Home Credit
5. ETL & Tableau
6. Citi Bike Poisson Regression
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