Exercises from Stanford University's Machine Learning Course by Andrew Ng on Coursera. This course covered Linear Regression, Gradient Descent, Logistic Regression, Support vector machines, and Artificial Neural Networks (backpropogation), all implemented from first principles. All done in Octave.
Nikil-Shyamsunder/ML-First-Principles
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