Introduction to Machine Learning with scikit-learn

Here you'll find a collection of follow-along files for machine learning with scikit-learn, all of which run in google colaboratory. These files are created by me, Michael Smirnov, and much of the content is based on the book "Hands-on machine learning with scikit-learn, Keras, and Tensorflow"

These files are meant to be consumed in the following order -

1. kaggle_titanic_prediction
2. multiclass_classification_decision_boundaries
3. svm_and_nonlinear_classification
4. ensemble_learning
5. unsupervised_learning
6. unsupervised_learning_2_images

Find more descriptions of the material, along with other tips and tricks, visit my blog here: michaelsmirnov.com

For the next set of follow-along tutorials, follow this-here link: https://github.com/mikeusru/neural-network-training

References:

Géron, Aurélien. Hands-on machine learning with Scikit-Learn, Keras, and TensorFlow: Concepts, tools, and techniques to build intelligent systems. O'Reilly Media, 2019.