How Do You Get AI Into Production?

In the ever-evolving landscape of technology and Generative AI, integrating DevOps principles into the machine learning (ML) lifecycle is a transformative game-changer.

Join me for an insightful session where we will explore essential aspects such as mlflow, deployment patterns, and monitoring techniques for ML models. Gain a deeper understanding of how to effectively navigate the complexities of deploying ML models into production environments. Discover best practices and proven strategies for monitoring and observing ML models in real-world scenarios.

By attending this session, you will acquire valuable insights and practical knowledge to overcome the unique hurdles of scaling and bringing AI into production. Unlock the full potential of your ML models by embracing the powerful integration of DevOps principles. This presentation is based on the extensive customer research I conducted to write the Best Seller book - Scaling Machine Learning with Spark - https://www.amazon.com/Scaling-Machine-Learning-Spark-Distributed/dp/1098106822.

About Adi Polak

Adi is an experienced Software Engineer and people manager. For most of her professional life, she has worked with data and machine learning for operations and analytics. As a data practitioner, she developed algorithms to solve real-world problems using machine learning techniques and leveraging expertise in Apache Spark, Kafka, HDFS, and distributed large-scale systems.

Adi has taught Spark to thousands of students and is the author of the successful book — Scaling Machine Learning with Spark. Earlier this year, she embarked on a new adventure with data streaming, specifically Flink, and she can't get enough of it.

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