Introduction to Machine Learning in R
|Royal Statistical Society|
Dr Colin Gillespie or Dr Jamie Owen
19/10/2021 - 20/10/2021
12 Errol Street/Online
View in Google Maps (EC1Y 8LX)
This is a two day course covering the application of machine-learning methodology to real-world analytics problems. The course outlines the stages involved in a machine learning analysis, and walks through how to perform them using the R programming language and the tidymodels suite of packages by Rstudio. Participants will be provided with exercises to complete in R, as well as interactive quizzes so as to gain hands-on experience in using the methods presented.
The individual stages of: problem formulation, data preparation, feature engineering, model selection and model refinement will be walked through in detail giving participants a solid process to follow for any machine-learning analysis. This includes methods for evaluating machine-learning models in terms of a performance metric as well as assessing bias and variance.
Delegates are expect to bring a laptop with the R software installed.
Following this course the attendees will:
Machine Learning can be applied to data in a whole range of fields from Finance to Pharmaceutical, Retail to Marketing, Sports to Travel and many, many more! This course is aimed at anyone interested in applying machine learning methods to their data in order to: gain deeper insight, make better decisions or build data products
This course assumes participants are comfortable with the basic syntax and data structures in the R language.
Intermediate (some prior knowledge)
£588 - £816 (inc. VAT)
Website and registration
Quantitative Data Handling and Data Analysis, R , Tidymodels , Machine learning , Problem formulation , Data preparation , Feature engineering , Model selection , Model refinement
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