Introduction to machine learning

Contains five machine learning exercises:

Polynomial regression in scikit-learn
Regression in scikit-learn on the Boston house-prices dataset
Classification in scikit-learn on the UCI Wine recognition dataset
Clustering and dimensionality reduction in scikit-learn using Fisher's Iris dataset
Hand-written digit classification in scikit-learn and Keras using the MNIST dataset

Name		Name	Last commit message	Last commit date
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.gitignore		.gitignore
0_intro_example_polynomial_regression.ipynb		0_intro_example_polynomial_regression.ipynb
1_intro_regression.ipynb		1_intro_regression.ipynb
2_intro_classification.ipynb		2_intro_classification.ipynb
3_clustering_dimred.ipynb		3_clustering_dimred.ipynb
4_deep_cnn_keras.ipynb		4_deep_cnn_keras.ipynb
LICENSE		LICENSE
README.md		README.md

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