What it's for

How many business decisions are made with data that's not quite right. The lack of a reliable predictive model can lead to misinformed choices and missed opportunities.

We tackle this by first framing the problem with stakeholders, identifying the key variables that drive the outcome we're trying to predict. Next, we collect and preprocess the relevant data, handling missing values and outliers as needed. We then train and test multiple machine learning models, selecting the one that best fits the data and meets the business needs. Finally, we deploy the chosen model in a suitable environment, such as a cloud-based platform or an on-premises server, and provide guidance on how to maintain and update it.

At the end of the project, the client has a fully functional predictive model, along with a detailed report outlining the methodology used, the data sources relied upon, and the performance metrics achieved. The model itself is also thoroughly documented, with commented code and clear explanations of how it works, allowing the client's team to understand and modify it as needed.

This service is designed for mid-sized Mexican companies that have a solid foundation in data collection and analysis, but are looking to take the next step by leveraging machine learning to drive more informed decision-making and improve their competitive edge.