Monetizing data within clear privacy and compliance regulations is a quintessential action for every company that wants to be or keep being relevant in their market. Analyzing data generated by everyday company activities might be one of the least expensive
At Xpand, we take pride in our XP4DS workflow and like to surround ourselves with the best tools to make our work easier and results better. Among those technologies and tools, MLFlow has special place reserved for it. If you haven’t heard
In the dynamic landscape of data science, building and deploying machine learning models is just the beginning. To ensure sustained success and optimal performance, continuous monitoring of these models is crucial. Model monitoring in the data science pipeline involves tracking,
A importância dos dados é amplamente reconhecida em vários setores e saber aproveitá-los representa um fator essencial que pode trazer uma vantagem competitiva substancial ou mesmo transformar a estrutura fundamental de uma empresa. A área da Data Science tem uma
You’ve spent weeks, maybe months, perfecting your machine learning model. The data is clean, the features are engineered and the model’s performance is stellar. But none of that really matters until your model is deployed – until it’s out there,
