Technical conferences evolve over time. They expand beyond their initial focus, adding new technologies, attracting new attendees and broadening their range of sessions and speakers. Formerly known as Spark + AI Summit Europe, the new Data + AI Summit Europe has embraced a data-centric approach — focusing on Apache Spark, MLflow and Delta Lake use cases; data engineering and Delta Lake infrastructure; SQL analytics, BI and data visualization; and machine learning automation, MLOps and AI use cases.
We are pleased to share the agenda for this year’s Data + AI Summit. You’ll see a range of sessions that focus on how to put the latest technologies and techniques into practice. With 125+ sessions, the event will cover the most popular open source projects in the industry, including Apache Spark, MLflow, Delta Lake, Koalas, TensorFlow, PyTorch and the Python data science ecosystem.
With this data-centric focus, the Summit aims to bring together data teams — data visionaries, Spark experts, machine learning developers, data engineers, scientists and analysts — to demonstrate innovation at scale, share how they solve tough problems and realize the full potential of data and AI.
AI, data, SQL and BI analytics, and other sessions by theme
Among the organizations presenting are Databricks, Microsoft, Facebook, Salesforce, IBM, Informatica, Walmart, H&M, Ernst & Young, SNCF, ByteDance, Intel, Lyft, CERN, Nielsen, Levi Strauss, Seldon, KTH, National University of Singapore, Stanford, University of KwaZulu-Natal, and many more. Topics and themes include:
- Automation and AI use cases: Learn how to use machine learning and other AI technologies to automate workflows, processes and systems. We have speakers from leading research groups and industry sectors, including IT and software, financial services, retail, logistics, IoT and media and advertising.
- 機械学習 and 深層学習: Explore tracks on popular libraries and tools, use cases and applications in forecasting and anomaly detection, recommenders, computer vision, and natural language processing.
- Building, deploying and maintaining data pipelines: As data and machine learning applications become more sophisticated, underlying data pipelines have become harder to build and maintain. We have a series of presentations on best practices for data engineering teams to build reliable data pipelines using Apache Spark and Delta Lake.
- MLOps and productionising ML: Choose from more than 20 presentations focusing on managing the machine learning development lifecycle, and how to deploy and monitor models once they’ve been deployed. This is an area where open source projects such as MLflow coupled with MLOps best practices are starting to emerge.
- Data management and platforms: Early in the year, Databricks introduced a new data management paradigm — Lakehouse — for the age of data, machine learning and AI. Summit features sessions that will examine the different components of a Lakehouse architecture, including data management and data ingestion.
- SQL analytics, BI and data visualization: We’ve expanded the conference with a focus on SQL and BI workloads. We will feature a dedicated track for data analysts, covering these use cases and related open source technologies like Redash.
- Training and deep dives: For developers, one of the most popular features of these conferences is training. Summit features a full day of training with courses in Delta Lake, Apache Spark 3.0, MLOps with MLflow, Deep Learning and Machine Learning with Apache Spark. And deep dives will immerse attendees into technical aspects of open source technologies such as Redash, Apache Spark, Delta Lake and MLflow.
- Spark performance and scalability: As always, Apache Spark will play a central role in Data and AI Summit Europe, with more than 20 sessions on scaling and tuning machine learning models, Spark SQL internals, and what’s new in Apache Spark 3.0.
Come and join us
Join the European data community online and enjoy the camaraderie at Data + AI Summit Europe 2020. Register to save your free spot!