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In this liveProject, you’ll go hands-on with supervised learning methods for anomaly detection. You’ll explore an imbalanced dataset of seismic activity. To balance this dataset you will utilize the SMOTE and ADASYN oversampling algorithms to both generate synthetic examples of the minority class and then compare performance using random forest, logistic regression and Naive Bayes binary classification algorithms.
This liveProject is for Python programmers who are interested in exploring machine learning. To begin this liveProject, you will need to be familiar with the following:
In this liveProject, you’ll master the domain of anomaly detection through exploring various methods.
geekle is based on a wordle clone.