Machine Learning using R and Concerto
Date:
14/09/2017 - 15/09/2017
Organised by:
University of Cambridge Psychometrics Centre
Presenter:
Dr Chris Gibbons, Aiden Loe
Level:
Entry (no or almost no prior knowledge)
Contact:
contact@psychometrics.cam.ac.uk
01223769483
Map:
View in Google Maps (CB2 3EB)
Venue:
Craik Marshall Building,
Department of Psychology,
Downing Site
Downing Street
Cambridge
Description:
This practical course will teach the fundamentals of data science, statistical and machine learning using the flexible R programming environment.
On day 1, users will learn how to manipulate datasets to gain valuable insights and visualise the data in an easy-to-understand manner. They will also learn how to extract data from the World Wide Web (i.e. Wikipedia, BBC) and a social media website by either scraping or via APIs (Twitter).
On day 2, users will be given a broad overview of the commonly used machine learning algorithms and be taught how to employ them in R. They will also be able to train their own text classification model and deploy it on the web as a tool for sentiment analysis.
The course assumes some level of R programming, but no direct experience in machine learning or statistical techniques. For those who are new to R, some additional materials will be given to you prior to the workshop so that you can get familiarise with the R syntax and working environment. There are no obligations to complete the additional materials but it will certainly hasten the learning pace during the workshop.
Those with experience in these domains will still be able to find challenging content and develop their knowledge under the supervision of the experienced University of Cambridge Psychometrics Centre staff.
Cost:
Business: £600 plus VAT
Academic: £400 plus VAT
Student: £300 plus VAT
Website and registration:
http://www.psychometrics.cam.ac.uk/trainingworkshops/MachineLearninginR
Region:
East of England
Keywords:
Quantitative Software, R, Machine Learning, Neural Networks, Concerto
Related publications and presentations: