- Scientific Computing
- Session type
- Technical level
Given a dataset, is it possible to automatically discover insights?
Can a machine analyse data and identify the most interesting patterns?
This talk walks through the basics of automated analysis techniques in Python that you can apply to most datasets.
The talk will cover:
- How to identify the numeric and non-numeric fields in a dataset
- The kinds of analyses that can be performed -- e.g. correlation, comparing means, etc
- How to identify the "interestingness" of each result, and show only the most interesting ones.
The analysis will entirely by in Python. NumPy and SciPy, in particular. Some samples of functions that'll end up being used are: scipy.stats.pearsonr, scipy.stats.kruskal, scipy.stats.ttest_ind, etc
Anand is a data scientist at Gramener, a data visualisation company. For more about Anand, visit http://s-anand.net/