Course Wiki
Introduction to Pandas — Machine Learning Zoomcamp Module 1
| ⚠️ | The notes are written by the community. If you see an error here, please create a PR with a fix. |
Related Pages
Machine Learning Zoomcamp › Module 1: Introduction to Machine Learning › Introduction to Pandas
Notes
Add notes here (PRs are welcome).
| ⚠️ |
The notes are written by the community. If you see an error here, please create a PR with a fix. |
Links
- Notebook from the video
- Notebook
Additional links
Key concepts
Related notes
- mlz-m01-crisp-dm
- mlz-m01-introduction-to-machine-learning
- mlz-m01-introduction-to-numpy
- mlz-m01-linear-algebra-refresher
- mlz-m01-ml-vs-rule-based-systems
- mlz-m01-model-selection-process
- mlz-m01-setting-up-the-environment
- mlz-m01-summary
- mlz-m01-supervised-machine-learning
- mlz-m02-baseline-model-for-car-price-prediction-project
- mlz-m02-categorical-variables
- mlz-m02-computing-rmse-on-validation-data
- mlz-m02-data-preparation
- mlz-m02-exploratory-data-analysis
- mlz-m02-feature-engineering
- mlz-m02-linear-regression
- mlz-m02-linear-regression-vector-form
- mlz-m02-regularization
- mlz-m02-root-mean-squared-error-rmse
- mlz-m02-setting-up-the-validation-framework
- mlz-m02-training-linear-regression-normal-equation
- mlz-m02-tuning-the-model
- mlz-m02-using-the-model
- mlz-m03-data-preparation
- mlz-m03-eda
- mlz-m03-feature-importance-churn-rate-and-risk-ratio
- mlz-m03-feature-importance-correlation
- mlz-m03-feature-importance-mutual-information
- mlz-m03-logistic-regression
- mlz-m03-model-interpretation
- mlz-m03-one-hot-encoding
- mlz-m03-setting-up-the-validation-framework
- mlz-m03-training-logistic-regression-with-scikit-learn
- mlz-m04-accuracy-and-dummy-model
- mlz-m04-confusion-table
- mlz-m04-cross-validation
- mlz-m04-roc-auc
- mlz-m04-roc-curves
- mlz-m04-summary
- mlz-m06-data-cleaning-and-preparation
- mlz-m06-decision-trees-parameter-tuning
- mlz-m06-gradient-boosting-and-xgboost
- mlz-m06-xgboost-parameter-tuning
- mlz-m08-installation-of-tensorflow
- mlz-m10-creating-a-pre-processing-service