Assistant Professor of Computer Science
Original Creator of Apache Spark & MLflow
Assistant Professor in Computing and Mathematical Sciences
Co-founder & CEO
Original Creator of Apache Spark
Co-founder & Chief Architect
Top Contributor & Original Creator of Apache Spark
Creator of scikit-learn
Brain Imaging Research
Principal Scientist at Google DeepMind
Principal Software Engineer
Corporate Vice President, Azure Data
Data and AI need to be unified: the best AI applications require massive amounts of constantly updated training data to build state-of-the-art models. So far. Apache Spark is the only unified analytics engine that combines large-scale data processing with state-of-the-art machine learning and AI algorithms.
The sessions and training at this conference will cover data engineering and data science content, along with best practices for productionizing AI: keeping training data fresh with stream processing, quality monitoring, testing, and serving models at massive scale. The conference will also include deep-dive sessions on popular software frameworks—e.g., TensorFlow, SciKit-Learn, Keras, PyTorch, DeepLearning4J, BigDL, and deep learning pipelines.
Combining Spark + AI topics, this conference is a unique “one-stop shop” for developers, data scientists, and tech executives seeking to apply the best tools in data and AI to build innovative products. Join more than 1,800 engineers, data scientists, AI experts, researchers, and business professionals for three days of in-depth learning and networking.
Spark + AI Summit 2019 begins on October 15, with several one-day training workshops, which will include both instruction and hands-on exercises. Apache Spark 2.4 certification is also offered as an exam, with an optional half-day prep course. Training and certification are available as add-ons to the conference pass.
Training courses at Spark+AI Summit utilize Databricks as courseware.
Apache Spark Developers
AI and Deep Learning Developers
Infrastructure / Site Reliability Engineers
Key Decision Makers