This web-post aims to provide a practical guide to Hypothesis Testing in Python; this is for testing for Statistically Significant differences between two situations or scenarios (it is more complicated if there’s more than two). This blog assumes little math or statistics background and doesn't attempt to prove or use the math theorems directly - … Continue reading Hypothesis Testing in Python
Machine Learning
Multivariable Regression with Python
The general linear model can be exteded from simple linear regression (which only has one predictor value) by adding other terms into the linear model. There is a nice blog article that digs deeper into some of the statistics here: http://connor-johnson.com/2014/02/18/linear-regression-with-python/ This article is a simpler layman's guide to multivariable linear regression with some basic techniques … Continue reading Multivariable Regression with Python
Simple Linear Regression with Galton
Introduction Although recent advances in Deep Learning neural networks get all the interest and air-time at the moment, many practical machine learning tasks can be achieved using simpler techniques. Linear Regression is relatively easy to understand and very effective for solving many prediction problems in an efficient way. This is a simple practical guide to … Continue reading Simple Linear Regression with Galton
Simple Machine Learning Prediction with the UN World Happiness Data-Set
Introduction This blog-post is the output from a Hackathon session with the Central London Data-Science Meetup Group. The task was to explore the World Happiness Data-Set published by the UN. The data provided includes a set of country metrics that are expected to influence general happiness and a separate summary survey “Happiness Score” for each country. … Continue reading Simple Machine Learning Prediction with the UN World Happiness Data-Set
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