(Reprint from a few years ago) Cameron is an open source contributor, a pythonista and a data geek – he’s developed various cool libraries. His blog is worth a read, and I personally recommend his screencasts. He’s got a strong Mathematical background like myself, and he currently is Lead Data Analyst in a Data Science job… Continue reading Interview with a Data Scientist – Cameron Davidson Pilon
You have a problem that you think might need some Bayesian modelling A common question I’m asked is how do you start? In this tutorial I take you from a fresh data set, the data set is an educational dataset. I don’t know anything about the data, and I have no specific domain knowledge. I… Continue reading How to build a bayesian model in 30 minutes?
I’ve been using Python for a number of years now – but like most things I didn’t really understand this until I investigated it. Firstly let’s introduce what a module is, this is one of Python’s main abstraction layers, and probably the most natural one. Abstraction layers allow a programmer to separate code into parts… Continue reading What happens when you import modules in Python
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
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
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
Yesterday evening I gave a talk at the Data Science Meetup in Luxembourg. This is part of my preparation for the talk at PyData the Python conference for Data Enthusiasts in Berlin. A few remarks – my slides from last night are here in IPython notebook format. I used for the presentation the excellent RISE… Continue reading Talk: Can Probabilistic Programming be applied to Rugby?
I’m happy to be a part of the PyData speaking community by speaking at my first PyCon. Here is the abstract and then some remarks 🙂 One of the biggest challenges we have as data scientists is getting our models into production. I’ve worked with Java developers to get models into production and there aren’t… Continue reading Speaking at PyData Track at PyCon Sei in Florence Italy