## Fun with MetOffice API’s

As a data scientist I often have to extract data from RESTful API’s this was something I’m admittedly not very good at. So I decided to look at the MetOffice Datapoint API  which provides weather information in the United Kingdom. You can visit that website to get your own API key if you wish. Being from…… Continue reading Fun with MetOffice API’s

## What I’ve been working on

This is just a little wrapper post to include some of the things I’ve worked on lately. I wrote up a short piece on Exploring new numpy features including the new matrix operator I wrote up some PyMC3 examples on my Github – this includes some Bayesian Logistic Regression and some classical examples of conversion modelling. I…… Continue reading What I’ve been working on

## Exploring the new NumPy features: Rewrite Python for Data Analysis

The new version of NumPy 1.10 contains the new Python @ operator. This is for matrix multiplication and greatly simplifies some code. This also appeals to me as a Math geek because it makes it really easy to write code down based on what you read in a paper. This makes implementing a linear algebra…… Continue reading Exploring the new NumPy features: Rewrite Python for Data Analysis

## Probability Inequalities: Why should I care

I wrote my Masters Thesis on Probability inequalities. This short gist is some notes I wrote up to help me remember the basics of probability inequalities. You may find it useful. https://gist.github.com/springcoil/819937924cdbd7d648e8

## Marketing data with PyMC3

My friend Erik put up an example of conversion analysis with PyMC2 recently. I decided to reproduce this with PyMC3. We want a good model with uncertainty estimates of various marketing channels. I’ll restate his assumptions for the model and then show the gist. Let’s make some assumptions about the model: The cost per transaction…… Continue reading Marketing data with PyMC3

## Interview with a Data Scientist: Brad Klingenberg

Bio Brad Klingenberg is the Director of Styling Algorithms at Stitch Fix in San Francisco. His team uses data and algorithms to improve the selection of merchandise sent to clients. Prior to joining Stitch Fix Brad worked with data and predictive analytics at financial and technology companies. He studied applied mathematics at the University of…… Continue reading Interview with a Data Scientist: Brad Klingenberg

## Interview with a Data Scientist: Alice Zheng

I recently caught up with Alice Zheng a Director of Data Science at Dato – Alice is an expert on building scalable Machine Learning models and currently works for http://www.dato.com who are a company providing tooling to help you build scalable machine learning models easily. She is also a keen advocate of encouraging women in…… Continue reading Interview with a Data Scientist: Alice Zheng