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Why keep learning?

ML practice evolves quickly. Staying current on delivery, risk and cost management helps your projects stay responsible and valuable as tooling and regulation change.

Dive deeper: Additional learning materials

Articles and reports

• Identifying, assessing and mitigating ML risks - framework and case studies.
• Fair ML book - ethical risks, auditing and bias reduction.

Tools and resources

• Google Responsible AI toolkit - fairness, transparency and governance practices.
• AWS cost management - ideas for controlling training and inference spend (adapt to your cloud vendor as needed).