Darío Martínez
Darío is a Data Scientist, who is passionate about programming, statistics and business intelligence. He is quite the scientist; any piece of code can be manipulated to predict the future. The larger and messier the dataset, the better.
Machine Learning is more than loss minimisation
When you start learning and working on machine learning problems, you usually think that the most important machine learning skill to master is training the best model performing model. You learn and apply...
Evolving “DevOps” to “AIOps” in your data platform
The need for cutting-edge Data Platforms Data Platforms are crucial for enabling true digital transformation. They continuously evolve by adopting new, cutting-edge technologies, often via cloud virtualization. These rapid changes require a shift in focus to...
Do agile methodologies fit in data science environments?
Extracting knowledge from data involves ingesting raw data and preparing it before training a Machine Learning model to validate and deploy it. Apart from requiring base knowledge in fields such as programming...
Research documents clustering for CAMERA
The Horizon 2020 Coordination and support action CAMERA evaluates the impact of European mobility-related projects. The CORDIS database presents a high volume of unclassified project data to which manual methodologies would be impossible to apply due...
Today’s Machine Learning challenge: automating automation
Applying traditional Data Science pipelines to real-world business is extremely time-consuming, resource-intensive and challenging. It requires a number of multidisciplinary experts, including Data Scientists and Data Engineers, which are two of the...
