SKU/Artículo: AMZ-B0DD3TSGNP

Getting Started with NVIDIA GPUs : A Beginner’s Guide to AI Acceleration with python, C++ and Cuda

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Fuera de stock

Peso con empaque:
0.36 kg

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No

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Nuevo

Producto de:
Amazon

Sobre este producto

Install and configure NVIDIA GPUs with confidence
Understand CUDA Cores, Tensor Cores, RT Cores, and how they impact AI
Train deep learning and computer vision models on your own machine
Run LLMs locally using PyTorch, Transformers, and quantization
Optimize models for maximum speed using TensorRT, ONNX, and mixed precision
Deploy AI workloads from desktop to edge devices like Jetson
Clear hardware fundamentals: CUDA Cores, Tensor Cores, VRAM, bandwidth, architectures
Driver & CUDA setup without the headaches: avoid the Linux/Nouveau pitfalls
Hands-on CUDA C++ examples: write real GPU kernels step-by-step
Deep Learning with PyTorch: tensors, training loops, mixed precision, dataloaders
Computer Vision workflows: ResNet, EfficientNet, YOLO, augmentation, fine-tuning
LLM & NLP engineering: Transformers, quantization (4-bit, 8-bit), LoRA
Generative AI workflows: diffusion models, xFormers, ComfyUI, A1111
Model optimization & deployment: TensorRT, ONNX Runtime, Triton Server
Edge AI engineering: Jetson devices, power constraints, deployment pipelines

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Getting Started with NVIDIA GPUs : A Beginner’s Guide to AI Acceleration with python, C++ and Cuda

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