Transform your machine learning projects into successful deployments with Andy’s practical guide on how to build and scale solutions that solve real-world problems. The Second Edition of Machine Learning Engineering with Python is the practical guide that MLOps and ML engineers need to build solutions to real-world problems. It will provide you with the skills you need to stay ahead in this rapidly evolving field.
The book takes an examples-based approach to help you develop your skills and covers the technical concepts, implementation patterns, and development methodologies you need. You’ll explore the key steps of the ML development lifecycle and create your own standardized “model factory” for training and retraining of models. You’ll learn to employ concepts like CI/CD and how to detect different types of drift.
In this session, learn about the following things:
1. What is the difference between Data Engineer and ML Engineer?
2. How do you become/start a career in ML engineering?
3. What is the difference in roles between ML engineers and MLOps engineers? And what are the overlaps?
4. What is the most difficult part of building an ML pipeline?
5. What’s new in this edition?
During the live event, you can ask more questions! We will try to get all the questions answered during the event.
We will also giveaway Ecopies to 2 lucky winners during the session. Comment with #PACKT to enter the raffle
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