Google have released a Python to Go transcompiler

Google have released an open source project on GitHub called Grumpy that converts Python to Go, and then compiles it down to native code.

It’s an interesting development, but since they won’t be supporting C extension modules (which basically rules out all the scientific and machine learning libraries I use), it means I probably won’t end up using this new tool too much.

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Notes from ‘A Few Useful Things to Know about Machine Learning’

I was reading a paper by Pedro Domingos this evening which had some tips and advice for people using machine learning. I’ve written down some bullet points for my own reference and I hope someone else finds it useful. I know I’ve made some of the mistakes he gives advice about avoiding.

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Why I post my writing to Reddit

Recently, I helped establish BioSky – a website dedicated to making medical and health research accessible to people without a scientific background. As we’ve been adding content to the site, I’ve been posting the links to multiple social networks including Facebook, Twitter, LinkedIn and Reddit.

If I had to pick only one platform to use, it would undoubtedly be Reddit. I’ve had this view for a while, but a recent experience in the /r/Biology subreddit, where I posted an article explaining prions really solidified my opinion.

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Deep Learning PyData Talk

Deep learning is a type of machine learning based on neural networks which were inspired by neurons in the brain. The difference between a deep neural network and a normal natural network is the number of ‘hidden layers’ between the input and output layers.

I recently watched an excellent presentation on Deep Learning by Roelof Pieters titled ‘Python for image and text understanding; One model to rule them all!‘ I can recommend watching it, and I’ve written this post for me to put down a few of my own bullet points from the talk for future reference.

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Essential WordPress Plugins for Blogging

Over the past few years of blogging using WordPress I’ve found a number of essential plugins for the platform. I’ve written this post to provide as a resource for myself and others and will try to periodically update it if I find new/better plugins.

Plugins I’m using at the moment:

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Why I refused a job offer to teach corporate programming workshops

A couple of months ago I was approached by an organisation that provided programming training to staff at companies. They asked me if I was interested in becoming a trainer for them based on my experience running Software Carpentry workshops.

After seeking clarification and looking through the teaching materials, I refused.

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Essential Libraries for Data Science on a Mac

I recently ran a fresh install on my Mac and thought I’d take the opportunity to document the libraries and programs I find incredibly useful.

The Python libraries I’ll frequently pip3 install include:

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Excel confusing CSV file with SYLK file

I recently had an interesting experience whilst using pandas to write some data to a CSV file and then opening the file up with Excel to inspect its contents. To my surprise, I received a message from Excel informing me that I was attempting to open something called a ‘SYLK file’.

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Removing webpage newline characters in Python

An issue I recently came across whilst using the Python requests module was that while I was trying to parse HTML text, I couldn’t remove the newline characters ‘
‘ with strip().

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Best practices for data science with the Jupyter Notebook

I recently listened to a really interesting talk by Jonathan Whitmore where he discussed the approach his company has to working with data using the Jupyter Notebook. I’d recommend watching it, but I’ve made a brief summary below for my own future reference.

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