From Statistics To Machine Learning

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51-53 Hatton Garden

London

EC1N 8HN

United Kingdom

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Refunds up to 7 days before event

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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:

  • Terminology and jargon
  • Supervised and unsupervised learning
  • Ensembles, bagging and boosting
  • Neural networks, image data and adversarial thinking
  • AI and ethical concerns
  • Reinforcement and imitation learning
  • Big data's challenges, opportunities and hype
  • Speed and memory efficiency
  • Concepts of model building such as cross-validation and feature engineering
  • Options for software, outsourcing and software-as-a-service
  • Data science workplaces combining statistical expertise with machine learning: what makes them happy and healthy


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.

Date and Time

Location

etc Venues

51-53 Hatton Garden

London

EC1N 8HN

United Kingdom

View Map

Refund Policy

Refunds up to 7 days before event

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