Due to the structure of Machine Learning solutions, performing several explorations and evaluation tasks is inevitable. Due to this, we apply agile principles when developing our solutions. This allows us to:
The steps below are iteratively carried out according to the needs of the business challenge and the solution.
Last but not least. When the solution is in use, the gathered feedback serves us in two ways. First, we can use the feedback to optimize the model. Secondly, the feedback collected through traditional KPI dashboards shows the value of the solution and serves as input as to what should be focused on next.
By using Agile Machine Learning we ensure that we rapidly deliver tangible results with a measurable competitive advantage to your business. Iterative development enables your organization to respond and adapt according to business changes as well as new insights. We will be by your side to identify the problem at hand, develop an ML solution and ultimately help you scale this solution to your needs.