In this project I explore my photography work of the last five years with the help of machine learning algorithms. I trained a DCGAN model on my entire photography work and explored his different training stages. The model looks at the database and then tries to recreate pictures from it based on what it learned. I'm interested to see what the machine will see as a feature and learn from my images. The first experiment showed me that it can learn light shading pretty good and basic composition. Some of the generated images definitely give me a feel similar to the original work. This work will surely be pushed forward in the future through more experiments. I am trying to have a better understanding of what the machine can learn and how we can use these algorithms creatively.