Learning is a huge part of who I am—I consider myself a Philomath, a lover of learning. As such, I am constantly looking for the next revolution in studying, knowledge and otherwise building some sort of skill.
I am becoming increasingly convinced that Machine Learning, specifically Deep Learning will have a huge impact on how we live our lives in the future. Powerful networks of algorithms have the potential to drastically alter the worlds we live in and I still believe the use of computers is vastly underestimated by most, especially the nature of employment and what it means to ‘do work’.
To this end, I am focusing on learning some of the basics of machine/deep learning to ensure I am somewhat familiar with the processes the technology uses. I hope that by having some baseline level of understanding I can continually build skill and not be left behind in what I ultimately may be a winner-take-all scenario for software and algorithms.
I hope to discuss more of these beliefs but also to write about the more practical aspects of these learnings—I am aiming to document each small project I do, along with the rationale behind why I felt the particular project was important and what I learned from it. In this way, I hope that it may serve as an entry point for others who may be interested in learning these kinds of skills—I am starting from a position without any formal education in Computer Science or similar skillsets, so should serve as a good indication of how difficult these projects will be to the general public.
- Machina 1—AI Twitter bot: Feb 4th, 2020
Below are the resources I’ve used to better understand machine learning:
- Google’s ‘Machine Learning Crash Course’A practical and fairly straightforward introduction to the very basics of machine learning. Highly recommend.