Introduction to machine learning
|Dates:||24 October 2022|
|Times:||13:00 - 14:00|
|What is it:||Webinar|
|Organiser:||Cathie Marsh Institute for Social Research|
What is machine learning? How is machine learning different from classic statistics? What are its applications? What type of models exist within machine learning?
If these are questions that you have then come along to this free three-part webinar that has been designed to deepen your understanding of the main concepts present within machine learning. Machine learning combines statistics and computer science to draw inference from patterns in data. It has now become an indispensable skill for data scientists and statisticians alike. These webinars, organised by the UK Data Service, will explore a few of the most important machine learning algorithms and then discuss model selection and evaluation of these models.
More specifically, our first session, on 24 October, 13.00 - 14.00, introduces the main concepts in machine learning. We tackle the big machine learning questions, like:
• what is a ‘model’?
• what is the difference between a supervised model and an unsupervised model?
Our second session, on 26 October, 13.00 - 14.00, moves on to exploring a specific unsupervised method, clustering. We will cover the following types of clustering algorithms:
• centroid-based: specifically, k-means algorithm
• hierarchical-based: divisive (top-down) and agglomerative (bottom-up)
We will then finish, on 1 November, with a live code demonstration in both R/RStudio and Python, using a customer dataset to put the theory into practice. Feel free to join the demonstration in your language of choice. The first half of the code demo, 13.00 - 14.00, will be in Python and the second half, 14.00 - 15.00, will be in R.
More information and booking at https://ukdataservice.ac.uk/events/introduction-to-machine-learning/
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