At this stage, you create and fine-tune the ML model and integrate it into your business processes:
Use the prepared data to train the models. This process involves selecting algorithms, adjusting parameters, and evaluating model performance.
- Integration into Business:
After training, the model is integrated into the process. This can mean automating routine tasks, predicting demand, optimizing resources, and other practical scenarios.
Therefore, proper implementation of AI in business requires thorough preparation, careful tool selection, and continuous updating and optimization of models to achieve maximum efficiency and competitive advantage in today's corporate environment.