https://github.com/noahgift/ml-engineer-certification
Notes on Google ML Engineer Certification
https://github.com/noahgift/ml-engineer-certification
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Notes on Google ML Engineer Certification
- Host: GitHub
- URL: https://github.com/noahgift/ml-engineer-certification
- Owner: noahgift
- License: cc0-1.0
- Created: 2022-06-16T14:01:17.000Z (over 3 years ago)
- Default Branch: main
- Last Pushed: 2022-07-23T20:29:14.000Z (about 3 years ago)
- Last Synced: 2025-01-12T15:33:04.854Z (9 months ago)
- Size: 6.84 KB
- Stars: 6
- Watchers: 2
- Forks: 1
- Open Issues: 0
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Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# ml-engineer-certification
Notes on Google ML Engineer Certification
## Framing ML Problems
* [framing](https://developers.google.com/machine-learning/crash-course/framing)
### 01: Translating business challenges into ML use cases
* Problem type (e.g., classification, regression, clustering)
* classification
* regression
* clustering
* Outcome of model predictions
* Input (features) and predicted output format
### 02: Defining ML problems
Alignment of ML success metrics to the business problem
Key results
Determining when a model is deemed unsuccessful
### 03: Defining business success criteria
Alignment of ML success metrics to the business problem
Key results
Determining when a model is deemed unsuccessful
### 04: Identifying risks to the feasibility of ML solutions
Assessing and communicating business impact
Assessing ML solution readiness
Assessing data readiness and potential limitations
Aligning with Google’s Responsible AI practices (e.g., different biases)
## References
* [Professional Machine Learning Engineer](https://cloud.google.com/certification/machine-learning-engineer)