On the other hand, i’m fairly bored-out at work and so, maybe I already mentioned it before, got myself in some mess 9 months ago by following a course in Machine learning & Deep learning. In Python. I didn’t knew shit about Python. I found energy there and paused the record label for now. Missing lots of energy, slowly getting it back by writing this newsletter.
Short: Building the machine learning models is doable but how to make it actionable and above all economical interesting is extremely hard. Deep learning is even harder. And you need lots of data. Half of current industries need an analytical translator to source the data first & help them turn it into a proof of concept before to dive into machine or deep learning. The things you read are a lie.
I’ve learned so much in the last few months, which made me think about how only a few people really make things actionable & economically interesting. I think it’s fair to say that we’re often waste our time thinking about non important stuff. Efficient leverage over time vs effective effort.