nvidia-dli

Practice exercises and assessments for NVIDIA DLI's "Fundamentals of Accelerated Computing with CUDA Python" course.

Resources and Learnings from NVIDIA Deep Learning Institute Training on "Rapid Applications Development with Large Language Model" by Vadim Kudlay

GPU-accelerated road network graph analytics pipeline — SSSP, 5-metric centrality analysis, and nx-cugraph backend methods, inspired by NVIDIA DLI. / NVIDIA DLI 학습 기반 GPU 가속 도로망 그래프 분석 파이프라인 — SSSP · 중심성 5종 · nx-cugraph 백엔드 3방식 구현.

repo for applications

My implementation of NVIDIA's "Generative AI with Diffusion Models" course. Built a DDPM (Denoising Diffusion Probabilistic Model) from scratch using PyTorch to generate handwritten digits from the MNIST dataset. Includes U-Net architecture, classifier-free guidance, and achieves 95%+ classifier accuracy.

Implementation of deep learning concepts based on NVIDIA DLI curriculum. Includes exercises on Neural Network training, Convolutional Neural Networks (CNNs), Pre-trained Models (VGG16/ResNet), and deployment using Python and PyTorch/TensorFlow

NVIDIA DLI 딥러닝 입문(Getting Started with Deep Learning) 한국어 강의 학습 노트