I find it useful for morale just to write up what I’ve been working on and what I’ve learned over the last few months.
PyMC3: Bayesian Logistic Regression: Bayesian Logistic Regression and Model Selection – I wrote an example of how to use Deviance Information Criterion for model selection in a Bayesian Logistic Regression. This example includes quite a few plots and visualisations in Seaborn.
Rugby Analytics: A Hierarchical Model of the Six Nations 2015 in PyMC3. This is based on the work I showcased at my talks, I finally got it into the PyMC3 Examples directory.
Comparison of Fibonacci functions – This is a classic interview question but I was interested in putting together an example comparing different data structures in Python. In particular this was a good exercise to make sure I understood lazy evaluation.
Hamiltonian Monte Carlo – I wrote up some notes on the Hamiltonian Monte-Carlo algorithm. This is used a lot in PyMC3 but I hadn’t gone through the theory before. The piece isn’t original but I thought it was worth putting on my blog.
Deep Learning – I wrote a short post based on a days work on getting Deep Learning to work on AWS. My advice is don’t re-invent the wheel and some of the Nvidia drivers are incredibly difficult to install. I was able to finally get GPU speedup and reproduce some examples from Tensorflow.
The Setup – I interviewed myself with my own version of the ‘Setup’ a noted website. This is just me talking about what tools I use both software and hardware. I found it useful to think about how my tools affect my thought processes and creativity so I recommend you do it too 🙂
Hacking InsideAirBnB – I was using AirBnB over the last few months, so I thought it would be good to look for examples of data sources. This isn’t a very complete Machine Learning project but I put it here anyway. I might fix it up and add some more feature extraction, visualisation and PCA/SVD type tools to this.
Image Similarity Database – I haven’t had the chance to work with image data much professionally. So when I came across this from my friend Thomas Hunger I forced myself to reproduce it. I used Zalando image data in this example.
Three Things I wish I learned earlier about Machine Learning – I first got interested in Machine Learning in 2009 when I was interning in Shanghai. I think the only notable work I did back then was using Matlab to do some simple clustering algorithms for customer segmentation. I don’t claim several years professional data-science or Machine Learning experience but I’m not a complete neophyte, and this article is just about what I’ve learned. I republished it on Medium too, so pick whichever version you prefer.
Dataconomy – I interviewed Kevin Hillstrom a consultant in Analytics, he discussed the need for accuracy and business acumen, which certainly applies to Data Analytics.
What does Big Data have to do with the Food Industry – I wrote a non-technical article on the opportunities for Data Science in the Food industry, this was the first time my commentary was featured on IrishTechNews.
There’ll be more stuff from me soon.
