Managing Machine Learning Projects with Google Cloud
Business professionals in non-technical roles have a unique opportunity to lead or influence machine learning projects. If you have questions about machine learning and want to understand how to use it, without the technical jargon, this course is for you. Learn how to translate business problems into machine learning use cases and vet them for feasibility and impact. Find out how you can discover unexpected use cases, recognize the phases of an ML project and considerations within each, and gain confidence to propose a custom ML use case to your team or leadership or translate the requirements to a technical team.
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- Assess the feasibility of your own ML use case and its ability to meaningfully impact your business.
- Identify the requirements to build, train, and evaluate an ML model.
- Define data characteristics and biases that affect the quality of ML models.
- Recognize key considerations for managing ML projects.