Nos dernières nouveautés et articles sur l'IA

An introduction to Causal Inference, why it is needed in data science and how Machine Learning can help, with real-world applications and exciting research directions.

Learn how to monitor the drift of your ML models and make sure that it never gets out of control!

Exploring LLMs: Unveiling profound text generation via embeddings & attention, while navigating challenges in data use.

Discover the latest in MLOps with Craft AI. Elevate your data science workflows with enhanced observability, machine learning monitoring, and simplified usage.

Paris, 18 juillet 2023 - Craft AI reçoit un financement de 5,5 millions d’euros pour accélérer le développement de son IA générative spécialisée dans la création de jeux de données. Ce financement, qui s'ajoute aux 9 millions déjà levés, se compose de 1,5 million d’euros provenant de l’appel à projet i-Démo de Bpifrance ainsi que de 4 millions d’euros apportés par la holding d’investissement Talis.

MLOps, short for Operational Machine Learning, is a practice that combines DevOps principles with the development and deployment of Machine Learning models. By automating and streamlining the entire lifecycle, from data preparation to model scaling, MLOps enables organizations to effectively leverage data for real-time, large-scale ML applications. In this context, Python libraries like Pandas and Polars play a crucial role, offering powerful data processing capabilities. Comparing these libraries helps optimize MLOps workflows, ensuring efficient and successful ML deployments.