Materials for the Learn PyTorch for Deep Learning: Zero to Mastery course.
$ npx skills add mrdbourke/pytorch-deep-learningAlternatives
Compare similar skills by workflow fit, trust score, quality, GitHub adoption, maintenance, and install readiness.
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Code Repository for Machine Learning with PyTorch and Scikit-Learn
Materials for the Learn PyTorch for Deep Learning: Zero to Mastery course.
$ npx skills add mrdbourke/pytorch-deep-learningA scikit-learn compatible neural network library that wraps PyTorch
$ npx skills add skorch-dev/skorchAI实战-practicalAI 中文版
$ npx skills add MLEveryday/practicalAI-cnONNX Runtime: cross-platform, high performance ML inferencing and training accelerator
$ npx skills add microsoft/onnxruntimepytorch handbook是一本开源的书籍,目标是帮助那些希望和使用PyTorch进行深度学习开发和研究的朋友快速入门,其中包含的Pytorch教程全部通过测试保证可以成功运行
$ npx skills add zergtant/pytorch-handbookPyTorch入门教程,在线阅读地址:https://datawhalechina.github.io/thorough-pytorch/
$ npx skills add datawhalechina/thorough-pytorchCLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image
$ npx skills add openai/CLIPThe "Python Machine Learning (2nd edition)" book code repository and info resource
$ npx skills add rasbt/python-machine-learning-book-2nd-edition此项目是机器学习(Machine Learning)、深度学习(Deep Learning)、NLP面试中常考到的知识点和代码实现,也是作为一个算法工程师必会的理论基础知识。
$ npx skills add NLP-LOVE/ML-NLPThe "Python Machine Learning (3rd edition)" book code repository
$ npx skills add rasbt/python-machine-learning-book-3rd-edition:fire: Machine Learning Notebooks
$ npx skills add dair-ai/ML-NotebooksHummingbird compiles trained ML models into tensor computation for faster inference.
$ npx skills add microsoft/hummingbirdPretrain, finetune ANY AI model of ANY size on 1 or 10,000+ GPUs with zero code changes.
$ npx skills add Lightning-AI/pytorch-lightningDeep Learning for humans
$ npx skills add keras-team/keras邱锡鹏《神经网络与深度学习》(蒲公英书)理论书 v2 与通识版
$ npx skills add nndl/nndlGoogle Research
$ npx skills add google-research/google-researchHow to choose
Use an alternative when it has a clearer install path, higher trust score, fresher maintenance, or better platform fit for your current agent stack. Keep Machine Learning Book if it already passes your workflow test and repository review.
Next step
Open the compare page, test the install commands in a sandbox, and check each repository before using a skill in production.