AI Adventures in Azure: Blob storage

My AI for Earth project is quite memory intensive so I have been learning about ways to take the data storage off the local disk and into the cloud, while still maintaining on the fly access to crucial files on my virtual or local machine. My classification problem started off requiring just a few GB … Continue reading AI Adventures in Azure: Blob storage

Heliguy Blog: Drones for Climate

UK drone company Heliguy recently ran a blog article about my work with drones in the Arctic including on my Microsoft/National Geographic AI for Earth grant. Drones have been increasingly important in my work on Arctic climate change, especially in mapping melting over glacier surfaces and as a way to link ground measurements with satellite … Continue reading Heliguy Blog: Drones for Climate

Eyes in the Sky 2: Airspace

Just like the land and oceans, the sky is divided into regulated regions. This makes sense, as it prevents unauthorised flights over sensitive and/or dangerous areas like airports, military zones, power stations, private land etc. Knowing the airspace classification is a fundamental prerequisite for making safe and legal flights with an unmanned aerial system (UAS). … Continue reading Eyes in the Sky 2: Airspace

Eyes in the Sky 1: METAR

I'm currently studying for my CAA permission for commercial operations (PfCO) - what is commonly thought of as the UK drone pilot's license. Flying small unmanned aerial systems (SUAS) is an increasingly common part of field science especially in polar science where a) scaling in-field observations over space is critical, b) we rely heavily on … Continue reading Eyes in the Sky 1: METAR

AI Adventures in Azure: Ice Surface Classifiers

For this post I will introduce what I am actually trying to achieve with the AI for Earth grant and how it will help us to understand glacier and ice sheet dynamics in a warming world. The Earth is heating up - that's a problem for the parts of it made of ice. Over a … Continue reading AI Adventures in Azure: Ice Surface Classifiers

AI Adventures in Azure: Ways to Program in Python on the DSVM

Having introduced the set up and configuration of a new virtual machine and the ways to interact with it, I will now show some ways to use it to start programming in Python. This post will assume that the VM is allocated and that the user is accessing the VM using a remote desktop client. … Continue reading AI Adventures in Azure: Ways to Program in Python on the DSVM

AI Adventures in Azure: Uploading data to the VM

There are many ways to transfer data from local storage to the virtual machine. Azure provides Blob storage for unstructured data managed through the user's storage account as well as specific storage options for files and tables. There is also the option to use Data Lakes. These are all useful for storing large datasets and … Continue reading AI Adventures in Azure: Uploading data to the VM

AI Adventures in Azure: Choosing VM Size

The main purpose of a VM is to accelerate scripts compared to running locally on a laptop or desktop by outsourcing the computation to a more powerful remote computer. There is an overwhelming number of options for Azure VM sizes, each of which is optimised for a particular purpose, so to get the best performance … Continue reading AI Adventures in Azure: Choosing VM Size

AI Adventures in Azure: Accessing the VM via terminal or remote desktop

Accessing the Data Science Virtual Machine Once the virtual machine is set up and started (by clicking “start” on the appropriate VM in the Azure portal) there are several ways to interface with it. The first is via the terminal (I am running Ubuntu 16.04 on both my local machine and the virtual machine). To … Continue reading AI Adventures in Azure: Accessing the VM via terminal or remote desktop

AI Adventures in Azure

A lot of my work at the moment requires quite computationally heavy geospatial analysis that stretches the processing capabilities of my laptop. I invested in a pretty powerful machine – i7-7700GHz processor, 32GB RAM – and sped things up by spreading the load across cores and threads, but it can still be locked up for … Continue reading AI Adventures in Azure