The Fifth Elephant 2013

1. Understand time series analysis and its applications in industry and science. Uncover patterns in data - trends, seasonality, cyclical behavior.

2. Learn intuitive visualization techniques. Methods for noise reduction, clustering of time series using shape analysis.

3. Catch the R ‘forecast’ package in action.

Outline

Description : A time series is a sequence of observations which are ordered in time (or space). Examples of time series data include -

Business data - demand data, sales, inventory management.

Neuroscience data - EEG, EKG

Financial data - stock prices, currencies, derivatives

Climate data - tide levels, sunspots.

You will learn how to approach time series analysis, extract patterns and make predictions that have a huge impact.

Requirements

Not a prerequisite, but exposure to R will help.

Speaker bio

I work as a data scientist at a large consulting firm where we are frequently consulted on time series forecasting problems. This talk is distilled out of my experiments with time series analysis and learnings so far.

I am a functional programming enthusiast who has ventured into machine learning and data analysis. At my previous company Runa I worked on machine learning while hacking lisp! I’d be happy to share my experiences with Clojure and self-learning adventures in data analysis as well.

Links

• http://www.linkedin.com/profile/view?id=23596683&trk=tab_pro