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  • $1,999

Professional XGBoost Cohort + Consult

  • Course
  • 108 Lessons

6 weeks of professional tabular learning. Includes live Q&A. Homework and accountability. Includes private calls.
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Contents

Getting Started

Creating a GitHub Project to Store Your Homework
    Weekly Instructions and Success Tips for Your XGBoost Course

      Week 1: Python & Pandas Review

      Peer Review
        00-Intro.mov
        • 1 min
        • 78.7 MB
        01-Classes.mov
        • 9 mins
        • 456 MB
        02-Pipelines.mov
        • 2 mins
        • 152 MB
        03-Functions-Parameters.mov
        • 7 mins
        • 473 MB
        04-Lambda.mov
        • 9 mins
        • 725 MB
        05-Lambda-Pandas.mov
        • 11 mins
        • 885 MB
        06-Parameters.mov
        • 3 mins
        • 166 MB
        07-Unpacking.mov
        • 7 mins
        • 440 MB
        08-Assign.mov
        • 6 mins
        • 471 MB
        09-Plotting-Intro.mov
        • 4 mins
        • 269 MB
        10-Line-Plots.mov
        • 8 mins
        • 595 MB
        11-Bar-Plots.mov
        • 11 mins
        • 695 MB
        12-Histograms.mov
        • 5 mins
        • 411 MB
        13-Scatter-Plots.mov
        • 8 mins
        • 642 MB
        14-PCA.mov
        • 6 mins
        • 495 MB
        15-Conclusion.mov
        • 1 min
        • 40.9 MB

        Week 1: Homework & Cheatsheet

        01-Homework.ipynb
        • 30.6 KB
        01-pypd.ipynb
        • 1.31 MB
        01-python-pandas.pdf
        • 541 KB
        GMT20240723-150046_Recording_640x360.mp4
        • 38 mins
        • 107 MB

        Week 2: ML Fundamentals

        201-Intro.mov
        • 2 mins
        • 81.8 MB
        202-Regression.mov
        • 2 mins
        • 107 MB
        203-Linear-Regression.mov
        • 6 mins
        • 443 MB
        204-Tree-Models.mov
        • 8 mins
        • 575 MB
        205-Feature-Engineering.mov
        • 12 mins
        • 942 MB
        206-Pipelines.mov
        • 4 mins
        • 262 MB
        207-Categorical-Data.mov
        • 5 mins
        • 295 MB
        208-Missing-Data.mov
        • 3 mins
        • 139 MB
        209-Python-Transformers.mov
        • 2 mins
        • 55.8 MB
        210-Large-Pipelines.mov
        • 4 mins
        • 299 MB
        211-Splitting-Data.mov
        • 5 mins
        • 373 MB
        212-Conclusion.mov
        • 1 min
        • 56.3 MB

        Week 2: Notebooks

        02-ml.ipynb
        • 811 KB
        02-sklearn.pdf
        • 104 KB
        02-Homework.ipynb
        • 22.3 KB
        GMT20240730-150247_Recording_1920x1080.mp4
        • 53 mins
        • 345 MB

        Week 3: Tuning Models

        301-Intro.mov
        • 7 mins
        • 316 MB
        302-Basic-Model.mov
        • 2 mins
        • 152 MB
        303-Overfitting-Evidence-Classification.mov
        • 5 mins
        • 374 MB
        304-Objectives-Cls.mov
        • 2 mins
        • 116 MB
        305-XGB-Hyperparameters.mov
        • 9 mins
        • 694 MB
        306-Stepwise-Tuning-Cls.mov
        • 15 mins
        • 1.1 GB
        307-Stepwise-Decision-Tree.mov
        • 5 mins
        • 252 MB
        308-Regression-Data.mov
        • 2 mins
        • 93.6 MB
        309-Default-XGB-Regression.mov
        • 2 mins
        • 131 MB
        310-Overfitting-Reg.mov
        • 4 mins
        • 251 MB
        312-Stepwise-Tuning-Reg.mov
        • 4 mins
        • 96 MB
        311-Objectives-Reg.mov
        • 1 min
        • 37.3 MB
        313-Conclusion.mov
        • 1 min
        • 57.2 MB

        Week 3: Notebooks

        03-xgboost.ipynb
        • 1.02 MB
        03-Homework.ipynb
        • 18.7 KB
        03-hyperparams.pdf
        • 44.8 KB
        GMT20240806-150352_Recording_1920x1080.mp4
        • 26 mins
        • 192 MB

        Week 4: Model and Data Evaluation

        402-Tuned-Classifier.mov
        • 3 mins
        • 168 MB
        403-Classification-Metrics.mov
        • 5 mins
        • 390 MB
        404-Confusion-Matrix.mov
        • 2 mins
        • 65.3 MB
        405-ROC.mov
        • 13 mins
        • 1010 MB
        406-Precision-Recall-Curve.mov
        • 8 mins
        • 524 MB
        407-Cost-Model.mov
        • 6 mins
        • 490 MB
        408-Learning-Curve.mov
        • 3 mins
        • 196 MB
        409-Missing-Values.mov
        • 3 mins
        • 168 MB
        410-Duplicate-Values.mov
        • 8 mins
        • 314 MB
        411-Outliers.mov
        • 5 mins
        • 190 MB
        412-PCA.mov
        • 7 mins
        • 451 MB
        413-Regression.mov
        • 2 mins
        • 108 MB
        414-Correlation.mov
        • 7 mins
        • 502 MB
        415-Residual-Plots.mov
        • 4 mins
        • 230 MB
        416-Residual-Analysis.mov
        • 3 mins
        • 178 MB
        417-Residual-Metrics.mov
        • 6 mins
        • 435 MB
        418-Learning-Curve.mov
        • 5 mins
        • 231 MB
        419-Missing-Values.mov
        • 3 mins
        • 214 MB
        420-Duplicates.mov
        • 8 mins
        • 474 MB
        421-Outliers.mov
        • 4 mins
        • 259 MB
        422-PCA.mov
        • 7 mins
        • 241 MB
        423-Conclusion.mov
        • 1 min
        • 53.3 MB

        Week 4: Notebooks

        04-evaluation-quality.ipynb
        • 73.6 MB
        04-evaluation.pdf
        • 548 KB
        04-Homework.ipynb
        • 12.1 KB
        GMT20240813-150123_Recording_1920x1080.mp4
        • 17 mins
        • 83.5 MB

        Week 5: Interactions and Constraints

        501-Load-Regression.mov
        • 5 mins
        • 402 MB
        502-Feature-Importance.mov
        • 14 mins
        • 1.13 GB
        503-SHAP.mov
        • 26 mins
        • 2.1 GB
        504-PDP.mov
        • 5 mins
        • 334 MB
        505-Monotonic-Constraints.mov
        • 3 mins
        • 199 MB
        506-Classification.mov
        • 1 min
        • 13.4 MB
        507-Feature-Importance.mov
        • 2 mins
        • 87 MB
        508-SHAP.mov
        • 6 mins
        • 410 MB
        509-Monotonic-Constraints.mov
        • 2 mins
        • 134 MB
        510-Conclusion.mov
        • 1 min
        • 27.5 MB

        Week 5: Notebooks

        05-Homework.ipynb
        • 8.78 KB
        05-shap-constraints.ipynb
        • 2.49 MB
        05-SHAP.pdf
        • 991 KB
        GMT20240820-150333_Recording_1920x1080.mp4
        • 39 mins
        • 201 MB

        Week 6: Problematic Samples

        601-Kfold.mov
        • 16 mins
        • 659 MB
        602-PCA.mov
        • 5 mins
        • 258 MB
        603-Dupes.mov
        • 5 mins
        • 285 MB
        604-Sample-Weights.mov
        • 6 mins
        • 434 MB
        605-Regression.mov
        • 1 min
        • 15.8 MB
        606-Kfold.mov
        • 5 mins
        • 149 MB
        607-PCA.mov
        • 6 mins
        • 317 MB
        608-Sample-Weights.mov
        • 3 mins
        • 221 MB

        Week 6: Notebooks

        06-Homework.ipynb
        • 4.77 KB
        06-kfold.ipynb
        • 58.9 MB
        06-kfold.pdf
        • 93.7 KB
        GMT20240828-153553_Recording_1920x1080.mp4
        • 29 mins
        • 190 MB