machine-learning-zoomcamp/03-classification at master · nbk3004/machine-learning-zoomcamp · GitHub

Name		Name	Last commit message	Last commit date
parent directory ..
images		images
01-churn-project.md		01-churn-project.md
02-data-preparation.md		02-data-preparation.md
03-validation.md		03-validation.md
04-eda.md		04-eda.md
05-risk.md		05-risk.md
06-mutual-info.md		06-mutual-info.md
07-correlation.md		07-correlation.md
08-ohe.md		08-ohe.md
09-logistic-regression.md		09-logistic-regression.md
10-training-log-reg.md		10-training-log-reg.md
11-log-reg-interpretation.md		11-log-reg-interpretation.md
12-using-log-reg.md		12-using-log-reg.md
13-summary.md		13-summary.md
14-explore-more.md		14-explore-more.md
README.md		README.md
homework.md		homework.md
meta.csv		meta.csv
meta.json		meta.json
notebook-scaling-ohe.ipynb		notebook-scaling-ohe.ipynb
notebook.ipynb		notebook.ipynb

README.md

3. Machine Learning for Classification

3.1 Churn prediction project
3.2 Data preparation
3.3 Setting up the validation framework
3.4 EDA
3.5 Feature importance: Churn rate and risk ratio
3.6 Feature importance: Mutual information
3.7 Feature importance: Correlation
3.8 One-hot encoding
3.9 Logistic regression
3.10 Training logistic regression with Scikit-Learn
3.11 Model interpretation
3.12 Using the model
3.13 Summary
3.14 Explore more
3.15 Homework

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