MLOps Fundamentals or What Every Machine Learning Engineer Should Know
Room: Saphire B - PyData
Time: 14:30 - 14:55
In this talk, we will explore the rapidly evolving field of MLOps. I will delve into best practices and tools that are essential for building and deploying machine learning models. I will cover topics such as data management, hyperparameter tuning, model training and model deployment, also share the latest techniques and tools for streamlining these processes and discuss best practices for monitoring and maintaining machine learning models in production. Whether you are a seasoned machine learning practitioner or just starting out, this talk will provide insights and practical tips for building robust, scalable, and maintainable machine learning systems. Join me as we dive into the world of MLOps and explore the tools and techniques that every machine learning engineer should know.
I have over a decade of work experience in various data related fields: Data Analytics, Data Science, Machine Learning, Data Engineering, Cloud Engineering. For three years I have led teams working with Data and Infrastructure. Now, my goal is to help You Level Up and Succeed in these fields.