As a PhD student in Deep Learning, as well as running my own consultancy, building machine learning products for clients I’m used to working in the cloud and will keep doing so for production-oriented systems/algorithms. There are however huge drawbacks to cloud-based systems for more research oriented tasks where you mainly want to try out various algorithms and architectures, to iterate and move fast. To make this possible I decided to custom design and build my own system specifically tailored for Deep Learning, stacked full with GPUs. This turned out both more easy and more difficult than I imagined. In what follows I will share my “adventure” with you. I hope it will be useful for both novel and established Deep Learning practitioners.