Deep dives into AI engineering, machine learning, and production systems
Strategies and techniques for efficiently scaling transformer models in production environments with PyTorch.
Read MoreA practical guide to creating scalable and maintainable machine learning workflows on Kubernetes.
Read MoreModel compression and optimization strategies for deploying object detection on resource-constrained devices.
Read MoreComprehensive guide to parameter-efficient fine-tuning of large language models using LoRA and QLoRA.
Read MoreDeep dive into the mathematical foundations and practical implementations of diffusion models for image generation.
Read MoreEssential tools, frameworks, and workflows for modern AI engineering and maximum productivity.
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