DVC provides the elements for managing machine learning pipelines using git repositories as a backend. If you use git for tracking your machine learning experiments, you will feel comfortable with DVC.[9min read]
Notebooks rule! We agree on that, but they can get messy very fast. The truth is they are not the best tool for good software engineering practices. Data Version Control (DVC) is a toolset for helping the development of machine learning experiments favoring better practices. Are you ready to give it a try? [5min read]
Are there any tangible benefits for the IT sector when hiring university graduates? A two-year program can fill the industry's needs?. The latter are valid questions that we should ask ourselves if we want to bring the university to current times. [6min read]
Tree-based algorithms suffer from severe limitations when applied to forecasting problems. They can't predict beyond observed training data points values. However, not everything is lost. There are some alternative approaches to improve the performance of the tree-based algorithm under such scenarios. [5min read]
The Software Industry has well-defined standards and procedures which are heavily based on tools such as Gitlab. However, in research sometimes we follow a more relaxed and not structured way. At LABSIN we have recently begun to apply software industry approaches to our daily work. The match is not perfect since research could be different in some way. But, the benefits are clear. [9min read]
