MLOps in the Wild

MLOps is a set of practices and tools that aims to streamline and automate machine learning models' deployment, management, and monitoring in production environments. MLOps bridges the gap between data scientists and IT/DevOps teams, enabling collaboration, scalability, and reliability in the machine learning lifecycle.

During this meetup, experts from AWS & CloudZone will present AWS SageMaker and its features and how it can be used to perform highly scalable and automated ML Operations through a customer story (LSports). In addition, we will dive into the fascinating world of Data Reliability Engineering and explore the critical role of Data Reliability Engineering (DRE) in successful Machine Learning implementations.

Agenda

Architecting a solid MLOps Foundation for Your Business
Boaz Horev, Sr. Solutions Architect, AWS

In this session, we will survey different MLOps architectures for different organization sizes and maturity levels. We leverage Amazon SageMaker's purpose-built tools and built-in integrations with other AWS services to accelerate the adoption of ML across the enterprise.

Automate Your Model Training with SageMaker Pipeline
Asaf Abres, MLOps & Data Engineer, CloudZone

SageMaker is a fully-managed AWS service for machine learning operations. The platform enables data scientists and machine learning engineers to rapidly innovate solutions through a fast, agile, scalable AWS service. During this meetup, we will focus on AWS SageMaker and how it can enhance your MLOps capabilities and create an automated pipeline for model training.

Transforming Data Science with AWS SageMaker: From Prototype to Production
Zvi Ben Ami, Senior Data Scientist, LSports

Lsports will provide an in-depth exploration of the data scientist's experience in developing machine learning models using AWS SageMaker. Participants will gain valuable insights into the end-to-end workflow, encompassing data preparation, model development, training, and deployment. Discover how SageMaker simplifies complex tasks, automates processes, and enhances overall productivity for data scientists.

Data Reliability Engineering: The Secret to Reliable Products
Oz Levi, EVP Data Operations Center Lead, CloudZone

In this lecture, we unpack the critical role of Data Reliability Engineering (DRE) in successful Machine Learning implementations. We'll explore how DRE assures data quality, performance, and consistency to enhance Machine Learning reliability, giving you key strategies to apply in your own data ecosystem.