Oregon State University 4 credits CS
Explores machine learning basics (variance and bias, underfitting and overfitting, etc). Reviews linear algebra and Numpy. Examines k-nearest neighbors, linear classification (perceptron and online learning), and linear and non-linear regression. Explores applications in housing price prediction (Kaggle contest) and text classification (sentiment analysis).
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