From Statistics To Machine Learning

Robert is the founder and Data Sherpa at BayesCamp, providing training in data visualisation, data analysis software and Bayesian models. He also provides one-to-one coaching for people working in data analysis. He has worked and taught in healthcare and other statistical applications for twenty years.

Robert Grant

This one-day workshop on 28 October is aimed at anyone who studied some statistics in the past, and wants to understand the principles of machine learning. There are a number of techniques and ways of thinking that can be useful in any form of data analysis. We will combine discussions about theory and working practices with thought-provoking small-group exercises. You will learn about: 
<UL>
<LI>Terminology and jargon</LI>
<LI>Supervised and unsupervised learning</LI>
<LI>Ensembles, bagging and boosting</LI>
<LI>Neural networks, image data and adversarial thinking </LI>
<LI>AI and ethical concerns </LI>
<LI>Reinforcement and imitation learning</LI>
<LI>Big data's challenges, opportunities and hype</LI>
<LI>Speed and memory efficiency</LI>
<LI>Concepts of model building such as cross-validation and feature engineering</LI>
<LI>Options for software, outsourcing and software-as-a-service</LI>
<LI>Data science workplaces combining statistical expertise with machine learning: what makes them happy and healthy</LI>
</UL>
 You can bring a laptop to try out some of the examples in R, but this is not essential. Refreshments, lunch, and even breakfast before the course begins, will be provided free of charge. Robert Grant is a medical statistician by training, more recently involved in machine learning techniques, who runs his own training and coaching company, BayesCamp. His specialities are Bayesian modelling (he is one of the contributing developers of Stan) and data visualisation (his book "Data Visualization: charts, maps and interactive graphics" is on CRC Press). He is currently test-driving around 20 different commercial machine learning software packages with the aim of publishing reviews and comparisons. He has many years' experience of teaching introductory courses and is committed to making advanced data analysis accessible to everyone who's interested.

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From Statistics To Machine Learning

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From Statistics To Machine Learning

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