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.
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.
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.
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:
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.
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:
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’.
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().
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.