ClearML: Your R&D on MLOps! From zero to hero in two lines of code
summary
ClearML is an open-source experiment + orchestration platform that the demo integrates with two lines of code to auto‑log runs, convert notebooks to runnable scripts, and capture artifacts and git commits. A ClearML agent on GPU nodes builds Docker images on the fly, pulls cached data, and performs one‑click remote launch; hyperparameter optimization runs use Optuna by default with parallelization and early stopping. Demo shows model lineage, runnable model artifact storage (100 GB free), pipelines and a working comparison UI; Kubernetes and on‑prem clusters are supported.
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chapters (18)
- 0:00Introduction to ClearML
- 1:47MLOps challenges in R&D
- 8:04Why use ClearML platform
- 11:55Getting started with ClearML
- 16:24Experiment tracking UI overview
- 17:08Two-line code integration demo
- 20:41ClearML Agent explained
- 23:32Remote experiment launching
- 26:19Summary and Q&A
- 27:00Hyperparameter optimization
- 39:03Sharing and collaboration
- 41:29Comparison and model management
- 44:38Community and future vision
- 46:06Private resource utilization
- 47:11Model deployment capabilities
- 49:40Pipelines and automation
- 50:44User personas and setup
- 53:13Closing and thanks
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