fix: update e2e-ml-workflow deps to fix deployment container crash

[Chakradhar886]

• Update conda.yaml: python 3.8->3.10, scikit-learn 0.24.2->1.5.1, numpy, scipy, pandas, azureml-mlflow versions aligned with sklearn-1.5
• Update Environment: base image ubuntu20.04->ubuntu22.04, remove hardcoded version to avoid stale cached environments
• Update workflow: python-version 3.8->3.10 (3.8 EOL, sklearn-1.5 requires 3.9+)

Root cause: data prep environment (python 3.8, sklearn 0.24.2) was incompatible with curated sklearn-1.5 training environment, causing 502 liveness probe failure on deployment container startup.

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