🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models
$ npx skills add MAIF/shapashAlternatives
Compare similar skills by workflow fit, trust score, quality, GitHub adoption, maintenance, and install readiness.
Current skill
A game theoretic approach to explain the output of any machine learning model.
🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models
$ npx skills add MAIF/shapashCLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image
$ npx skills add openai/CLIPMaterials for the Learn PyTorch for Deep Learning: Zero to Mastery course.
$ npx skills add mrdbourke/pytorch-deep-learning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-NLPTensorFlow documentation
$ npx skills add tensorflow/docsAI实战-practicalAI 中文版
$ npx skills add MLEveryday/practicalAI-cnCode Repository for Machine Learning with PyTorch and Scikit-Learn
$ npx skills add rasbt/machine-learning-bookThe fastai book, published as Jupyter Notebooks
$ npx skills add fastai/fastbookpytorch 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-pytorch12 Weeks, 24 Lessons, AI for All!
$ npx skills add microsoft/AI-For-BeginnersGoogle Research
$ npx skills add google-research/google-research⛔️ DEPRECATED – See https://github.com/ageron/handson-ml3 or handson-mlp instead.
$ npx skills add ageron/handson-mlThe fastai deep learning library
$ npx skills add fastai/fastaiThe "Python Machine Learning (2nd edition)" book code repository and info resource
$ npx skills add rasbt/python-machine-learning-book-2nd-editionFree online textbook of Jupyter notebooks for fast.ai Computational Linear Algebra course
$ npx skills add fastai/numerical-linear-algebraHow 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 Shap 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.