At Positronic we take a four-step approach to implementing a new data science project.
First, we go through our DISCOVER process where we visually navigate the available data looking for patterns and correlations and we apply advanced analytics and visualizations as a guide to building hypotheses for what sorts of predictive models may fall out of the data. Second, we test chosen hypothesis through TEST. A test is a unitary data research project over a big data collection. Often data cleanup and augmentation is required to piece together a viable dataset for learning. The test process explores all relevant machine learning models to generate mathematical proof of efficacy. Third, we BUILD an API from a model with proven efficacy and refine it with further training until the model achieves the desired level of accuracy and performance on new unseen data. Finally, our cloud apps team partners with your engineering and IT teams to DEPLOY the new interfaces into an existing line of business app or a new cloud app.
Looking for technical experts to serve as your AI sherpas as you guide your organization down this path? Contact our team to learn about process - and to start with an audit of your current data and automation potential. Positronic.AI