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

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2. A/B test

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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

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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