2 个仓库
Awesome GitHub RepositoriesDeep Learning Environment Setup
Guidance and scripts for installing the software stack and acceleration libraries required for deep learning development.
Distinct from Build Environment Configurators: Focuses on the full stack installation for AI research (drivers, CUDA, PyTorch) rather than generic build-time flags or OS package configuration.
Explore 2 awesome GitHub repositories matching development tools & productivity · Deep Learning Environment Setup. Refine with filters or upvote what's useful.
Awesome Deep Learning Environment Setup GitHub Repositories
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- xiaotudui/pytorch-tutorial
xiaotudui/pytorch-tutorial
4,195在 GitHub 上查看本项目是一个 PyTorch 深度学习教程和教育资源。它提供了一个结构化的课程和分步指南，用于从零开始设计、训练和验证神经网络。 该资源包含关于计算机视觉实现的具体指南，重点介绍使用卷积神经网络进行目标检测和图像分类。它还提供了通过硬件加速优化模型性能以缩短训练时间的说明。 这些材料涵盖了完整的模型开发生命周期，包括张量运算、图像数据集准备，以及损失函数和优化器的使用。它还通过保存和重新加载训练好的权重来解决模型生命周期管理问题。
Offers guidance and scripts for installing the PyTorch software stack and hardware acceleration libraries.
Pythonpytorchpytorch-tutorial - fo40225/tensorflow-windows-wheel
fo40225/tensorflow-windows-wheel
3,672在 GitHub 上查看This project provides precompiled TensorFlow binary distributions as Python wheels for Windows. It is designed to enable the installation of the TensorFlow framework without requiring manual compilation from source. The distribution specifically includes non-AVX builds, providing a machine learning runtime compatible with legacy or low-end CPUs that do not support AVX instructions. These packages facilitate machine learning environment setup and AI development workflows on Windows by offering ready-to-use binaries for rapid installation.
Facilitates deep learning environment setup on Windows using ready-to-use binary wheels.
Pythonbinarybuildcpp
