INFOMDA1 Review Notes
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    • General
    • README

    👉0 Content

    • 0. SLV General

    👉1 Resources

    • 1 Resources - 考前必打开网页
    • 1.1 SLV Course Homepage - Example Codes
    • 1.2 ChatGPT - Answers
    • 1.3 Example Exam - Question Types, For Review
    • 1.4 Cheatsheets

    👉2 Exam Qs

    • 2. Exam Questions
    • 2.1 Theoretical - Data Visualization
    • 2.2 Theoretical - Improving Plot, Explaining
    • 2.3 Theoretical - Energy Prediction
    • 2.4 Practical - Decision Rule
    • 2.5 Practical - LASSO

    👉3. Topics & Codes

    • 3. Content
    • 3.1 Data Wrangling - 数据类型,新建,摘要
    • 3.2 Graphics - 绘图
    • 3.3 EDA - 查看、探索数据
    • 3.4 Linear Regression - CI, MSE, Split, Cross Validation
    • 3.5 Classification - KNN, Confusion Matrix, LR, LDA (Used For Predicting Categorical Variables)
    • 3.6 Classification Evaluation - Confusion Matrix, LR, LDA, Classification Trees, Random Forest
    • 3.7 Nonlinear Regression - Prediction Plot, Poly
    • 3.8 Ensemble Methods - Bagging, RF, Boosting, Xgboost

    On this page

    • INFOMDA1-review-notes

    README

    INFOMDA1-review-notes

    This is my review notes for the course INFOMDA1. It has been deployed on https://infomda1.netlify.app/docs/general/.
    Since you've found my wonderful notes, I believe we can all pass the course!
    If you feel that this notes has helped you, feel free to drop me a message at kloudyes[at]gmail.com :-)