Starting machine learning
February 16, 2019
For a few years now, I’ve been sitting here wishing that I knew machine learning. Yearning for a job where I was looking at data and writing algorithms to find patterns and make predictions.
But the problem is exactly that. I’ve been sitting and wishing, not learning and doing. True, I did a course on Coursera a few years ago, but that hardly cuts the mustard. So I’ve decided that now it’s my time. I would really like to get into it, and so here’s my commitment to myself to do it.
I don’t mean just watching videos and reading books, or even creating pretty visualisations or learning how to throw something together using Scikit Learn. I want to know what’s going on so that I can make good and informed decisions, communicate them, and (perhaps one day!) become a data scientist.
One of the best ways that I know to be sure that I know material, and can talk about it confidently, is to talk about it. So that’s what I’ll be doing. Talking about it. Writing about what I’ve learnt, am learning, insights that I’ve had. Consolidating my knowledge. Who knows, there may be some cool visualisations too.
What I must remember along this journey (huge note to self) is that if this is going to be successful, I need to just do it. The aim is not to write lecture notes or a book. This is reinforcement learning (pardon the pun), and it’ll only work if I reinforce the learning – i.e. just write. As such, if you’re reading this, please don’t expect any kind of order!
To get started, I’ll be working my way through An Introduction To Machine Learning.