To the Stars
This post reviews the purpose, aims and learning outcomes of the OU module TU812 Managing Systemic Change: inquiry, action and interaction (OU, 2010) to act as an ongoing reference point for me during my studies.
Key themes of the module:
Change, what it is and how to manage it in an inter-connected world.
Managing change is meant, in terms of this module, as having a positive bearing on change, in both its nature and direction. [Read more…] about Aims and Learning Outcomes
One of my fellow students on the Managing Systemic Change module I’ve just started studying recommended mendeley.com as a great free resource (provided by the academic publisher Elsevier) for bookmarking, annotating, organising and quickly/easily citing from academic papers in your area of study or research. It looks like a great tool so I decided to sign up and start using it. [Read more…] about Defining a multi-disciplinary field
I never really wrote much about my explosive ‘career-reset’ moment of late last year. On one level it was brought about by the equally-explosive changes taking place at the company where I worked, and an increasing realisation that I was neither value-aligned nor in agreement with their strategic direction. (There were other reasons too which I can’t go into in a public forum at this time.) But it was just as much caused by the slow simmer of change that’s been brewing in my personal life – no, let’s say “in my true self” – for a good few years now. [Read more…] about Meta-morphosis
Here is a growing list of resources related to Systems Theory, Systems Thinking and Systems Practice.
Introductory Level:
Dipping a toe in the Udacity pool:While I’m not yet skilled or experienced enough at this time to lead a session, I felt really excited that I might have an opportunity to be a session supporter and assistant. That would be cool as I’d be exploring and networking in such an important growth area in tech skills, as well as supporting the growth of MOOCs here in London, which is something I feel really passionately about. [Read more…] about Machine Learning Engineering
Here’s a quick revision and recap on some basic maths and linear algebra needed when studying Machine Learning. This will covers basics of calculus and linear algebra. A future post will revise some basic statistics, then I’ll go on todo some quick example calculations of standard deviations, derivatives and matrix determinants.
1. Linear Algebra – matrix multiplication:
Matrices can basically be though of as arrays of numbers, which might be a simple array (equating to a list in Python) which can be expressed as a simple one-row or one-column matrix:
, or they might be more complex matrices with multiple rows or columns: [Read more…] about Mathematics Mondays (revising some basics)
Data analysis process:The process we’ve been using during the capstone course – and in line with the original Page/Brin search engine process – is to first collect the raw data and store it – unprocessed – into a holding database. From here we’ve gone on to clean up the data and save it in a more structured way in a new, relational database. This results in a smaller database which is quicker to search and retrieve data from. As I found when writing my own search engine application, these first two databases take a long time to retrieve the data, especially when the search engine’s reach is set widely. [Read more…] about D3.js and Data Visualisation