docs: Add detailed use case sections for training, inference, and MLOps

Add comprehensive documentation extracted from V3 example notebooks
covering all training, inference, and MLOps use cases with V3 code
examples. New sections include local container training, distributed
training, hyperparameter management, JumpStart, custom InferenceSpec,
model optimization, inference pipelines, processing jobs, batch
transform, model registry, Clarify, EMR Serverless, MLflow integration,
and lineage tracking. Each section includes red NEW highlights for
change detection and expanded V2-to-V3 migration tables.

Author: nargokul

docs/_static/custom.css

@@ -172,3 +172,21 @@ p {
     font-size: 1.0rem;
     color: var(--pst-color-text-base);
 }
+
+/* NEW CONTENT HIGHLIGHT - remove this block to revert red highlighting */
+.new-content {
+    border-left: 4px solid #dc2626;
+    padding-left: 16px;
+    margin-left: 0;
+}
+.new-content-label::before {
+    content: "NEW";
+    background: #dc2626;
+    color: white;
+    font-size: 0.7em;
+    font-weight: 700;
+    padding: 2px 8px;
+    border-radius: 3px;
+    margin-right: 8px;
+    vertical-align: middle;
+}