Machine Learning Notebooks

A series of Jupyter notebooks, to know about Machine Learning, its implementation, and identifying its best practices.

This project aims at walking you through the fundamentals of Machine Learning.

Name		Name	Last commit message	Last commit date
Latest commit History 23 Commits
01-linear-regression		01-linear-regression
02-detect-and-remove-outliers		02-detect-and-remove-outliers
03-normality-and-transformations		03-normality-and-transformations
04-feature-scaling		04-feature-scaling
05-polynomial-features-and-regularizations		05-polynomial-features-and-regularizations
06-cross-validation		06-cross-validation
07-hyperparameter-tuning		07-hyperparameter-tuning
08-logistic-regression		08-logistic-regression
09-k-nearest-neighbors		09-k-nearest-neighbors
10-support-vector-machine		10-support-vector-machine
11-decision-tree		11-decision-tree
datasets		datasets
LICENSE		LICENSE
README.md		README.md

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