Hi all, my name’s Alex and I’m a final year Mathematics student at Leeds uni in the UK. During my degree have started programming, mostly in Python (a little in R) and would say I know my way around the basics fairly well (classes are still sorcery to me at the moment) but my main knowledge is out of a necessity to do maths. I’ve done a couple of larger projects including my dissertation/final year project on network dynamics which involved implementing simple algorithms to model opinion dynamics. The other project was a summer research project about random forests and decision trees and relied heavily on the machine learning library scikit learn, which allowed me to jump right into machine learning without understanding all that much. A combination of this and watching endless interviews with Demis Hassabis of Deepmind has inspired me to crack on and dive deeper into machine learning.
The intention of this blog is to share and document the process of learning more programming and machine learning as I go from Zero to Machine Learning Hero (lame attempt originality is a work in progress). Hopefully this will provide me with motivation for a developing hobby and, at a later date, even be a source of inspiration and information for other. With this in mind I’ll provide links to resources I have found useful and (maybe) explanations of new things what I learnt in attempts to solidify my own understanding. I’m currently relying on the books Introduction to/Elements of Statistical Learning (ISL/ESL) as well as the Google Developers machine learning series.
- Python classes
- My first ‘home grown’ machine learning algorithm, i.e. not using the inbuilt classifiers of sklearn
- Wade through ISL/ESL
That concludes the obligatory first post, time to get started on classes, next post will no doubt be about that.