MLOps with Data Version Control: Creating & Using DVC Pipelines
MLOps 2023
| Expert
- 12 videos | 1h 21m 21s
- Includes Assessment
- Earns a Badge
Data Version Control (DVC) pipelines empower data practitioners to define, automate, and version complex data processing workflows. By streamlining end-to-end processes, pipelines enhance collaboration, maintain data lineage, and enable efficient experimentation and deployment in data-centric projects. In this course, you will discover the intricacies of machine learning (ML) pipelines within DVC. You will set up a pipeline with data cleaning, training, and evaluation stages and run these stages using the dvc repro command. Then you will use DVC to track the status of the pipeline with the help of the dvc.lock file. Next, you will run and track a DVC pipeline as an experiment using DVCLive and view metrics and artifacts of your pipeline in the Iterative Studio user interface. Finally, you will queue DVC experiments so they can be run later, either in parallel or sequentially. This course gives you an in-depth understanding of DVC pipelines, equipping you to seamlessly orchestrate and manage your ML workloads.
WHAT YOU WILL LEARN
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Discover the key concepts covered in this course
Set up a data version control (dvc) project for a machine learning (ml) pipeline
Track training data in dvc
Add a data process stage to an ml pipeline
Run a pipeline stage
Add a train stage to an ml pipeline -
Run multiple pipeline stages
Add an evaluation stage to an ml pipeline
Remove a duplicate dvc.yaml file
Run dvc experiment pipelines
Queue and run experiments sequentially and in parallel
Summarize the key concepts covered in this course
IN THIS COURSE
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1m 54sIn this video, we will discover the key concepts covered in this course. FREE ACCESS
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6m 43sFind out how to set up a Data Version Control (DVC) project for a machine learning (ML) pipeline. FREE ACCESS
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3. Tracking Training Data with DVC6m 53sIn this video, you will learn how to track training data in DVC. FREE ACCESS
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4. Adding the Data Process Stage to the ML Pipeline9m 31sDiscover how to add a data process stage to an ML pipeline. FREE ACCESS
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5. Executing Pipeline Stages10m 11sDuring this video, you will learn how to run a pipeline stage. FREE ACCESS
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6. Adding a Train Stage to the ML Pipeline6m 56sIn this video, find out how to add a train stage to an ML pipeline. FREE ACCESS
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7. Executing the Data Process and Train Stages6m 41sDuring this video, discover how to run multiple pipeline stages. FREE ACCESS
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8. Adding and Executing the Evaluate Stage in a Pipeline10m 22sLearn how to add an evaluation stage to an ML pipeline. FREE ACCESS
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9. Eliminating a Duplicate dvc.yaml File5m 18sFind out how to remove a duplicate dvc.yaml file. FREE ACCESS
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10. Running DVC Experiment Pipelines8m 35sIn this video, discover how to run dvc experiment pipelines. FREE ACCESS
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11. Queueing and Running Experiments6m 22sDuring this video, you will learn how to queue and run experiments sequentially and in parallel. FREE ACCESS
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12. Course Summary1m 54sIn this video, we will summarize the key concepts covered in this course. FREE ACCESS
EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE
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