How to get started with data science in containers

4.2.2016

The biggest impact on data science right now is not coming from a new algorithm or statistical method. It’s coming from Docker containers. Containers solve a bunch of tough problems simultaneously: they make it easy to use libraries with complicated setups; they make your output reproducible; they make it easier to share your work; and they can take the pain out of the Python data science stack.

We use Docker containers at the heart of Kaggle Scripts. Playing around with Scripts can give you a sense of what you can do with data science containers. But you can also put them to work on your own computer, and in this post I’ll explain how.

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Innovation policy, and Jupyter notebooks

8.12.2015

I’ve written a couple of new things: one on the government’s new innovation package, and one on Jupyter notebooks.

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What to expect from Morrison as Treasurer

22.9.2015

Scott Morrison is a formidable politician, a leading contender to replace Tony Abbott, and perhaps the anointed successor to Malcolm Turnbull. But Treasury is hardly an easy stepping-stone to the Lodge. Of the 38 Treasurers before Morrison, only six went on to be Prime Minister. The portfolio is complex, technically demanding, and affected by short-term economic conditions that are out of the Treasurer’s direct control. What can we say about how Morrison’s tenure is likely to go?

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The rent is too damn high, and also not high enough

31.8.2015

News stories about Australia’s overheating real estate market have been missing a key part of the story. Rents in Sydney and Melbourne are far too expensive. On the other hand, they’re likely to increase even further. Unless we take action now, the poorest households could bear most of the pain of the property market rebalancing. As if that wasn’t reason enough, the state of the rental market will give the RBA a severe headache in the next few years, leading to tighter interest rates and an economy kept below its potential.

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3 data science skills that economists can use

8.8.2015
It’s big data, baby

I’ve been working as a data scientist for a little while now, and when I think back to my previous jobs in economics and econometric research, I realise that there are a few skills and practices that are common in data science which would have been really helpful. So I’m putting this listicle out there, in case it’s useful for anybody else.

The skills listed here have been included if, and only if, I reckon they’d be useful in applied economics.

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