Deep Learning

PyTorch 2.x Production Engineering Masterclass • Chapter 16 of 16 (Grand Finale) Production ML Engineering, MLOps & Grand Capstones Cross.

PyTorch 2.x Production Engineering Masterclass • Chapter 15 Modern Model Export: torch.export, AOTInductor, ONNX & ExecuTorch Master the complete enterprise.

Module 14 • Large-Scale Multi-GPU Distributed Systems Distributed Training in PyTorch: DDP, FSDP2, Tensor Parallelism & Parallelism at Scale Scale.

Module 12 • Modern LLM Engineering & Fine-Tuning Large Language Model Fine-Tuning in PyTorch: Hugging Face, PEFT, LoRA & QLoRA.

Module 11 • Generative AI Deep Engineering Generative Deep Learning in PyTorch: VAEs, GANs, WGAN-GP, and Diffusion Models (DDPM) Master.

PYTORCH 2.x MASTERCLASS • CHAPTER 7 Model Evaluation, Validation Protocols & Experiment Tracking A rigorous engineering guide to empirical model.

A complete, professional PyTorch Engineering Masterclass organized across 16 hands-on chapters. Start from tensor foundations and work your way up.

Complete PyTorch Series — Module 12 of 12 Building and training state-of-the-art models is only half the battle. In production,.

Complete PyTorch Series — Module 11 of 12 Deep neural networks often train for hours, days, or weeks across hundreds.

Module 13 • Compiler Engineering & Hardware Acceleration PyTorch 2.x Optimization: torch.compile, AMP Mixed Precision, CUDA Graphs & Profiling Unlock.