The uptake of machine learning (ML) has been slow in fields that use geospatially informed data, largely because mainstream ML libraries lack functionality for working with geospatial data. To this end, we are developing a step-by-step ML workflow that will walk users through data input, processing, training, interpretation, and deployment. It will include functionality for geospatial contexts, such as aligning coordinate reference systems. In addition to making geospatial machine learning and deep learning workflows accessible to those without a technical programming background, it will be available as a free and open-source software to promote open science and reduce access barriers.