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Content

This course will cover the basic components of building and applying prediction functions with an emphasis on practical applications. The course will also introduce a range of model based and algorithmic machine learning methods including regression, classification trees, Naive Bayes, and random forests. The course will cover the complete process of building prediction functions including data collection, feature creation, algorithms, and evaluation.

Johns Hopkins University

Teacher: Professor Roger D. Peng, PhD
Provided by: Coursera
Course language: English
Fees: free course
Level: intermediate
Certificate possible? (fee)
Format: MOOC/online course

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