A library of extension and helper modules for Python's data analysis and machine learning libraries.
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VIP cheatsheets for Stanford's CS 229 Machine Learning
A library of extension and helper modules for Python's data analysis and machine learning libraries.
$ npx skills add rasbt/mlxtendRay is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
$ npx skills add ray-project/rayPretrain, 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
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$ npx skills add yzhao062/pyodA python library for user-friendly forecasting and anomaly detection on time series.
$ npx skills add unit8co/dartsFast and Accurate ML in 3 Lines of Code
$ npx skills add autogluon/autogluonH2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.
$ npx skills add h2oai/h2o-3🏅 Collection of Kaggle Solutions and Ideas 🏅
$ npx skills add faridrashidi/kaggle-solutionsA fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP.
$ npx skills add microsoft/FLAMLStatistical Machine Intelligence & Learning Engine
$ npx skills add haifengl/smileTime series forecasting with PyTorch
$ npx skills add sktime/pytorch-forecastingProbabilistic time series modeling in Python
$ npx skills add awslabs/gluontsHow 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 Stanford Cs 229 Machine Learning if it already passes your workflow test and repository review.
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