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Description

Introduction to machine learning workshop given at HackPSU Spring 2022

Anaconda is required to follow along -- download here: https://www.anaconda.com/

Includes:

• ML-Workshop.ipynb: interactive presentation
• exam-scores.csv: dataset used in presentation
• figs: figures illustrating various algorithms

References

Code/data:

• Dataset modified from https://www.coursera.org/learn/machine-learning
• Decision boundary function based on https://www.udemy.com/course/machinelearning/

Figures:

• Animated gradient descent: https://alykhantejani.github.io/images/gradient_descent_line_graph.gif
• SVM kernel: https://link.springer.com/chapter/10.1007/978-981-15-7421-4_2
• Neural network: https://www.digitaltrends.com/cool-tech/what-is-an-artificial-neural-network/
• Nonconvex gradient descent: https://www.coursera.org/learn/machine-learning