Fundamentals of Machine Learning
Organizer: Royal Statistical Society
Venue: The Royal Statistical Society
Country: United Kingdom
Postcode: EC1Y 8LXDescription:
Presenters: Doug Ashton
CPD: 6 hours
This is a one day course covering the fundamentals of machine learning and the methodology for applying them 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 caret library. Participants will be provided with exercises to complete through the course so as to gain hands on experience in using the methods presented.
Be familiar with the overall process of how to apply Machine Learning methods in an analysis project Understand the differences and similarities between statistical modelling and machine learning theories Have gained hands on experience in working with the caret package in R Gain an intuitive understanding of how several specific machine learning methods solve the problems of prediction and classification
Machine Learning Classification and Prediction Feature Engineering Cross Validation Hyper-parameter Tuning Random Forests Gradient Boosting Support Vector Machines
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 has now reached capacity. We are next running this course on 24th October 2017.
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