Build your ML pipeline within an hour with this workshop and two practical exercises
- Why do you need a pipeline for Machine Learning models? Introduction to Machine Learning Operations (MLOps)
- What is Kedro: an open-source Python framework for creating reproducible, maintainable and modular data science code
- How to run ML pipelines on the cloud using Vertex AI on the Google Cloud Platform
- Get extra MLOps materials (2 practical exercises, MLOps Q&A)
About the MLOps Workshop:
This workshop was conducted recently as a live webinar organized by GetInData | Part of Xebia, which has massive experience with MLOps use cases. As it was a well-welcomed, highly rated, and widely commented event, we decided to share access to its recording (along with materials: two practical exercises and a supplement to the workshop: MLOps Q&A).
About the Speaker:
Michał Bryś
Machine Learning Engineer at GetInData | Part of Xebia, MLOps speaker. Since 2009 Michał has been helping companies to use their data to solve real business problems with Machine Learning. His toolbox contains TensorFlow, Python, Hadoop, Spark and all data processing tools on the Google Cloud Platform. He has no fear of petabyte scale data sets and low-latency systems. A Google Cloud Certified Professional Machine Learning Engineer.