This article belongs to a series of articles about MLOps tools and practices for data and model experiment tracking. In the first part, we explained why data and model experiment tracking was important, and how tools like DVC and Mlflow could solve this challenge....
With the rise of interest and the number of machine learning projects (self-driving car, facial recognition, recommendation systems), traditional software development has shifted from hard-coded rules to data-estimated rules a.k.a. data-driven models (cf. figure 1). A...
Nowadays, diversity is the holy grail of model accuracy: deep forest is a promising framework based on deep learning layers but without neurons and back propagation. The revolutionary deep forest frameworks enable the introduction of diversity as the tip of the...
Après avoir passé les 5 dernières années à travailler sous un environnement Linux / Unix, cette expérience m’a permis de me familiariser avec les interpréteurs de lignes de commandes (autrement appelé le terminal) et leur fonctionnement interne. J’ai tout de suite...
Aujourd’hui, Git est un des systèmes de contrôle de version les plus utilisés et les plus téléchargés au sein du secteur IT. Cependant, comme pour toutes les solutions, Git possède quelques lacunes qu’il est important de prendre en compte. Objectif : éviter de voir un...
You have been working on a proof-of-concept using a Machine Learning pipeline that is being scaled up ? Congratulations, you have done a wonderful job: only 13% of the data science project actually make it to production! Now you are being asked a lot of questions such...
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