Principles of Machine Learning (IN-PERSON)

Beginners

This is very much a first course on machine learning. It aims to provide a foundation for future work with machine learning. This course will get you to the point where you can confidently engage with literature referencing machine learning. We will be using the CARET package to apply some basic machine learning methods within R.

If you do not have a University of Cambridge Raven account please book or register your interest here.

If for any reason the above links do not work, please email Research Informatics Training Team with details of your course enquiry.

• ♿ The training room is located on the first floor and there is currently no wheelchair or level access.
• Our courses are only free for registered University of Cambridge students. All other participants will be charged according to our charging policy.
• Attendance will be taken on all courses and a charge is applied for non-attendance, including for University of Cambridge students. After you have booked a place, if you are unable to attend any of the live sessions, please email the Research Informatics Training Team.
• Further details regarding eligibility criteria are available here.
• Guidance on visiting Cambridge and finding accommodation is available here.

• Everyone is welcome to attend the courses, please review the relevant policies.

• This course requires users to be familiar with the R language. Attending an introductory course Introduction to R is advantageous if you do not have a working knowledge of R already.

Number of sessions: 1

Introduction to :

• cross validation
• random forests
• support vector machines
• neural networks
• k nearest neighbours
• k means clustering

To develop a comfort with the terminology and broad processes of Machine Learning

Presentations, demonstrations and practicals

Participants can make use of the computers in the training room.

This is subject to change in line with the training schedule.

• Free for registered University of Cambridge students
• £ 60/day for all University of Cambridge staff, including postdocs, temporary visitors (students and researchers) and participants from Affiliated Institutions. Please note that these charges are recovered by us at the Institutional level
• It remains the participant's responsibility to acquire prior approval from the relevant group leader, line manager or budget holder to attend the course. It is requested that people booking only do so with the agreement of the relevant party as costs will be charged back to your Lab Head or Group Supervisor.
• £ 60/day for all other academic participants from external Institutions and charitable organizations. These charges must be paid at registration
• £ 120/day for all Industry participants. These charges must be paid at registration
• Further details regarding the charging policy are available here

1

several times a year

• Introduction to R (ONLINE LIVE TRAINING)
• Intermediate Supervised Machine Learning (ONLINE LIVE TRAINING)