Saturday 23 Sep, 2017

Starting at 9am

Etc Venues

One Drummond Gate, Victoria, London SW1V 2QQ
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Advanced Machine Learning

About this course

Advanced 3 hours

Machine learning is becoming more and more popular as a tool for analysis. But there is a big gap between knowing a little bit about machine learning algorithms to being able to get the most out of these techniques in a business.

This is a guided practical course to give you experience in applying machine learning algorithms for applications like forecasting.

Background

Hierarchical (or multi-level) models provide a way of including and clarifying assumptions when trying to understand data. For example, you might want to assume that all products in a particular category are similar or that all variations in a split test will have something in common.
Combined with a Bayesian approach this gives a flexible way of building and validating models with many applications for digital businesses. One such application is in forecasting where the ability to include business specific assumptions in the model can make a big difference. Usual methods of calculating seasonality struggle with movable feasts (like Easter) let along more complicated issues such as new product launches or stock shortages.

Prerequisites

This is an advanced course, and attendees should have some familiarity with either R or Python. You will require a laptop with R, R Studio, Stan and Shinystan to fully participate in the course.

Trainer

Trainer_Richard-Fergie

Richard Fergie

@RichardFergie

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