Machine Learning
Machine learning workflows, GPU optimization, model deployment, and MLOps tools for modern AI applications
Introduction
Machine learning has evolved from research experiments to production systems that power modern AI applications. This comprehensive guide covers everything from GPU optimization and CUDA compatibility to production-ready MLOps workflows, helping you build scalable and efficient machine learning systems.
What You'll Learn
This section covers essential machine learning concepts and tools:
- GPU Optimization - CUDA compatibility and performance tuning
- LLM Inference - High-performance model serving with VLLM
- MLOps Tools - MLflow, Kubeflow, and workflow management
- Model Deployment - Production-ready ML model serving
- Performance Tuning - GPU utilization and optimization strategies
- Workflow Automation - End-to-end ML pipeline orchestration
- Tool Comparison - Choosing the right MLOps solution
Tags: #MachineLearning #MLOps #GPUOptimization #ModelDeployment #LLM #Inference #CUDA #VLLM #MLflow #Kubeflow #AI #DeepLearning #ProductionML