Meet the community.

Cornerstone OnDemand is a cloud-based human resource software. Their data science team regularly deal with textual data and have a lot of interdependent models. Current model deployments solution on the market didn't really cover their need which is why the team at Cornerstone decided to build their own in-house framework: modelkit. On top of using the library internally they recently decided to open-source the solution and in this talk they will introduce us to the library.

Long-tail events modeling is at the core of Descartes Underwriting's products. This requires the use of time series extensions and advanced statistics, the tooling required for this goes beyond your vanilla python's stack for data science. In this talk, Descartes' CTO, Alexandre Cameron, will tell us the story and show some concrete examples of the in-house framework they developed to solve the challenges associated with optimising data management, packaging, deployment and visualisation in their specific context.

Let's meet from 8:30am to 10am to discuss real-world MLOps issues, around coffee, orange juice and croissants ☕

In this talk, we want to share our findings and experiences on building platform services for managing AI and ML-pipelines in an efficient manner. Using container-based technologies like Docker and Kubernetes we can improve the data scientists’ workflows without the need to know what happens in the background. It’s all about automation and self-service, whether it’s in the cloud or built as on-premises infrastructure. Managing data is also a very important yet often underestimated challenge to cover and talk about as this is the asset from which we generate the most value.

Data Drinks are monthly social gathering that brings together data professionals for interesting conversations.

ML development brings many new complexities beyond the traditional software development lifecycle. MLflow is an open-source project from Databricks aiming to solve some of these challenges such as experiment tracking, reproducibility, model packaging, deployment and governance, in order to manage and accelerate the lifecycle of your ML projects.

Data Drinks are monthly social gathering that brings together data professionals for interesting conversations.

Data Drinks are monthly social gathering that brings together data professionals for interesting conversations.

Data Drinks are monthly social gathering that brings together data professionals for interesting conversations.

Learn to serve Scikit-Learn models through a Flask REST API

• Modélisation sur Scikit-Learn : l'événement du jour sera d'autant plus focus sur le déploiement de votre modèle
• Création & déploiement d'un webservice Flask pour servir votre modèle de prédiction via une API rest
• Démo d'une solution de déploiement clé en main
• Echangeons autour d'un verre