MLOps. Machine Learning deployment: AWS, GCP & Apple in<6hrs
MLOps. Machine Learning deployment: AWS, GCP & Apple in<6hrs
Learn to deploy ML models to multiple environments, Data Engineering best practices and BOOST your career
Created by Maxim Migutin | 5 hours on-demand video course
– 08.2023: + New Extra materials in Chapters #3 & #7
– 10.2023: + “MLOps Market Overview” chapter.
Learn key Market stats, trends + Salaries & Role Expectations
– 11.2023: + “Data Drifts” section (+1 hour of content). Learn to discover data drifts & deal with them.
EvidentlyAI + MLFlow integration
MLOps has been helping me automate & roll out robust, easily maintainable and state-of-the-art ML in IT, Food and Travel industries over the last 6 years.
With the help of modern Cloud Computing and open source software I’ve brought live dozens of ML research projects, successfully solved very complex Business challenges and even changed the country where I live & work!
There are many different technologies powering modern ml ops. Some of them are: AWS Sagemaker, Kubeflow, Azure machine learning, mlflow, GCP Vertex AI, dvc etc. We will cover many of them and see how they work together.
The course will also teach you about Data Drifts: a common issue arising in the world of Machine Learning models. We will learn what these are, how to discover them in a timely manner and what actions to take to mitigate their effect on model’s performance.
We will use a variety techniques for that: from simple visual analysis using histograms & box plots all the way to learning EvidentlyAI.
Join me in this fun and Industry-shaped course to get new skills and improve your MLOps & Cloud acumen!
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What you’ll learn in MLOps Course
- Productionize ML Solutions to Real World Business Problems
- Roll out ML Models to Multiple Environments
- Learn to Work in AWS SageMaker
- Learn to Work in GCP Vertex AI
- Train & Deploy ML Models for Apple Devices
- Create a Solid Case to GET PROMOTED in Your Career
Who this MLOps course is for:
- Machine Learning Enthusiasts, Data Scientists, Data Analysts, Developers, AI professionals
