Cake for Classification

Overview

Classification is one of the most common—and critical—machine learning tasks. Whether you’re routing tickets, flagging fraud, detecting sentiment, or tagging customer records, classification models help teams turn messy data into actionable signals.

With Cake, you can quickly build and deploy classification models using proven open-source components. Train using frameworks like PyTorch or XGBoost, manage experiments in MLflow, serve models through scalable endpoints with KServe or Triton, and monitor performance over time—all orchestrated through Cake-native workflows.

Because everything is modular and cloud agnostic, you get full control over your stack without vendor lock-in. And with built-in support for lineage, versioning, and compliance, your models are easier to trust, reproduce, and improve over time.

Key benefits

• Accelerate model deployment: Go from experimentation to production faster using pre-integrated open-source tools.
  
  
• Adapt to your domain: Choose the best classification models and frameworks for your use case.
  
  
• Run anywhere: Deploy across cloud, on-prem, or hybrid environments with no lock-in.
  
  
• Monitor performance and drift: Track metrics over time and surface when predictions start to degrade.
  
  
• Build with compliance in mind: Capture model lineage, enable audits, and manage data access securely.