I've been in this business for years and the best (or worst?) thing is that once I gain enough experience to feel comfortable as an expert, something drastically changes and I feel like I have to start over again. It was like that when Python and Node started taking over C++ and Java market. Then it was like that when cloud platforms started taking over traditional hosting. Then machine learning started growing so much I had to keep up. Now, traditional ML seems passe. What's next? Quantum algorithms?
Learning your job again every couple of years is a bit concerning, but as much exciting. It's not a steady improvement, it's a constant fight. The current revolution gives great opportunities, but in the same time if you don't take this opportunity, you may stay behind. How not to? This article is not an answer, but it is an introduction to how I cope with it and stay competitive.
For the past couple of years I have been building ML models, experimenting with them, testing various model types, structures, parameters, validating, following best practices, building pipelines. I have been doing that at work, but I have also been doing that within my personal projects, which is my secret weapon. Personal projects is something I have been doing forever. I love to construct things that don't have to generate profit, but they help you answer the question 'what happens if I do that?'. This is the way to stay in touch with reality. When you join new teams and projects there are always great expectations, but the projects are not always fancy, ambitious, and satisfactory. Personal projects ensure you are always there with the global trends, not just the local needs. They let you invent new solutions, not just implement standards. They let you experiment on a level unreachable in commercial work.
