Machine-learning-notebooks

Kaggle kernels and the respective implementations of ML procedures taught in the course.

Important links of sklearn documentation for Decision trees, Random Forests, XGBoost etcetra.

Name		Name	Last commit message	Last commit date
Latest commit History 4 Commits
README.md		README.md
cross-validation.ipynb		cross-validation.ipynb
data-leakage.ipynb		data-leakage.ipynb
exercise-machine-learning-competitions.ipynb		exercise-machine-learning-competitions.ipynb
exercise-model-validation.ipynb		exercise-model-validation.ipynb
exercise-random-forests.ipynb		exercise-random-forests.ipynb
exercise-underfitting-and-overfitting.ipynb		exercise-underfitting-and-overfitting.ipynb
handling-missing-values.ipynb		handling-missing-values.ipynb
model-validation.ipynb		model-validation.ipynb
partial-dependence-plots.ipynb		partial-dependence-plots.ipynb
pipelines.ipynb		pipelines.ipynb
random-forests.ipynb		random-forests.ipynb
seaborn-tutorial-pokemon-dataset.ipynb		seaborn-tutorial-pokemon-dataset.ipynb
underfitting-and-overfitting.ipynb		underfitting-and-overfitting.ipynb
xgboost.ipynb		xgboost.ipynb
your-first-machine-learning-model-971761.ipynb		your-first-machine-learning-model-971761.ipynb