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Models are great on their own but you can make them better by combining them together! Ensemble methods are techniques in machine learning that help you do this.

Pipelines help turn buly and unwieldy machine learning workflows into shorter, interpretable, and reproducible processes that can be deployed to users. This course walks you though the major stages of building a pipeline for your machine learning project.

Includes Naive Bayes Classifiers, Support Vector Machines (SVM's), Hyperparameter Tuning, Boosting and Bagging, and more...

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Includes Python, Machine Learning, Software Engineering, Algorithms, Pandas, scikit-learn, Git, Bash, and more...

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