Dynamic Kubernetes Autoscaling with Custom Python Metrics

Create a Kubernetes horizontal pod autoscaler that uses custom Python-generated metrics from application performance monitoring. Develop a sidecar container that exposes application-specific performance indicators, implementing advanced scaling logic that considers both system metrics and business-specific performance thresholds. The solution should dynamically adjust pod replicas based on complex computational workloads, with built-in machine learning prediction of resource requirements.