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Develop Production-Level Machine Learning Models using MLRun
December 29, 2023
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For whom is this course?
Data Scientists and ML Engineers from students to seniors.
What will you learn?
What are good habits in the 3 phases of a model’s life cycle – Data Preparation, Development, and Deployment.
- How MLRun is built to adopt good habits into your work.
- How MLRun integrates into existing code and enables quality of life features like Automatic Logging, Model Management, and Distributed Training.
- Use MLRun’s model development tools to train classifiers on the classic, known, and loved Iris and MNIST datasets.
Prerequisites
- Install MLRun on your computer
- Work with Jupyter notebooks.
- Very basic SciKit-Learn and TensorFlow background.
Syllabus
- What is the model life cycle?
- MLRun – The Open Source MLOps Orchestration Framework.
- MLRun’s model development features – Automatic Logging, Model Management, and Distributed Training.
- Iris demo – Train and deploy an Iris classifier.
- MNIST demo – Train and deploy a handwritten digits classifier.
Instructors
Course Info
Certificateyes
Duration2 hours
Start DateJuly 10, 2022
Last Registration DateJuly 3, 2022
No of Students50
Skill Levelintermediate
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