In this workshop, we’ll cover best practices for enterprises to use powerful open source technologies to simplify and scale your ML efforts. We’ll discuss how to leverage Apache Spark™, the de-facto data processing and analytics engine in enterprises today, for data preparation as it unifies data at massive scale across various sources.
In this workshop, we will demystify DataOps & MLOps, discuss the basis for their sudden popularity and relevance, and walk you through in a hands-on fashion how they can be implemented in production. This workshop is designed to be a learning opportunity for practitioners like you, so please bring your laptop so you can work through the examples with us, live.
Join this half-day workshop to learn how unified analytics can bring data science and engineering together to accelerate your ML efforts. In this workshop, we’ll cover best practices for enterprises to use powerful open source technologies to simplify and scale your ML efforts. We’ll discuss how to leverage Apache Spark™, the de-facto data processing and analytics engine in enterprises today, for data preparation as it unifies data at massive scale across various sources.
Join this half-day workshop to learn how unified analytics can bring data science and engineering together to accelerate your ML efforts. In this workshop, we’ll cover best practices for enterprises to use powerful open source technologies to simplify and scale your ML efforts. We’ll discuss how to leverage Apache Spark™, the de-facto data processing and analytics engine in enterprises today, for data preparation as it unifies data at massive scale across various sources.
Join this half-day workshop to learn how unified analytics can bring data science and engineering together to accelerate your ML efforts. In this workshop, we’ll cover best practices for enterprises to use powerful open source technologies to simplify and scale your ML efforts. We’ll discuss how to leverage Apache Spark™, the de-facto data processing and analytics engine in enterprises today, for data preparation as it unifies data at massive scale across various sources.
Join this half-day workshop to learn how unified analytics can bring data science and engineering together to accelerate your ML efforts. In this workshop, we’ll cover best practices for enterprises to use powerful open source technologies to simplify and scale your ML efforts. We’ll discuss how to leverage Apache Spark™, the de-facto data processing and analytics engine in enterprises today, for data preparation as it unifies data at massive scale across various sources.
Join this half-day workshop to learn how unified analytics can bring data science and engineering together to accelerate your ML efforts. In this workshop, we’ll cover best practices for enterprises to use powerful open source technologies to simplify and scale your ML efforts. We’ll discuss how to leverage Apache Spark™, the de-facto data processing and analytics engine in enterprises today, for data preparation as it unifies data at massive scale across various sources.
L'équipe Databricks vous invite pour son évènement de rentrée sur les bords de Seine. Au programme: les dernières nouveautés Databricks, témoignage client et genius bars (Delta, Mlflow, UAP).
Cette soirée vous permettra également de rencontrer vos pairs dans un cadre convivial.
Inscrivez-vous et votre équipe!
Join this half-day workshop to learn how unified analytics can bring data science and engineering together to accelerate your ML efforts. In this workshop, we’ll cover best practices for enterprises to use powerful open source technologies to simplify and scale your ML efforts. We’ll discuss how to leverage Apache Spark™, the de-facto data processing and analytics engine in enterprises today, for data preparation as it unifies data at massive scale across various sources.
The idea of DevOps revolutionised software development by making it feasible to develop, integrate and test software in a continuous manner, resulting in faster time-to-value and a lower overall cost of deployment. The need to continually innovate with data in a production setting has led to the inception of two related concepts: “DataOps” and “MLOps”, which seek to bring these same benefits of reduced cycle times and reduced risk to the spheres of data analytics and machine learning, respectively.
In this workshop, we will demystify these two ideas, discuss the basis for their sudden popularity and relevance, and walk you through in a hands-on fashion how they can be implemented in production. This workshop is designed to be a learning opportunity for practitioners like you, so please bring your laptop so you can work through the examples with us, live.
