Alternatives
Compare similar skills by workflow fit, trust score, quality, GitHub adoption, maintenance, and install readiness.
Current skill
A curated list of Graph/Transformer-based fraud, anomaly, and outlier detection papers & resources
A Python library for anomaly detection across tabular, time series, graph, text, and image data. 60+ detectors, benchmark-backed ADEngine orchestration, and an agentic workflow for AI agents.
$ npx skills add yzhao062/pyodA python library for user-friendly forecasting and anomaly detection on time series.
$ npx skills add unit8co/dartsA unified framework for machine learning with time series
$ npx skills add sktime/sktimeRay 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
$ npx skills add keras-team/keras💫 Industrial-strength Natural Language Processing (NLP) in Python
$ npx skills add explosion/spaCyThe AI developer platform. Use Weights & Biases to train and fine-tune models, and manage models from experimentation to production.
$ npx skills add wandb/wandbLow-code framework for building custom LLMs, neural networks, and other AI models
$ npx skills add ludwig-ai/ludwigFast and Accurate ML in 3 Lines of Code
$ npx skills add autogluon/autogluonTechniques for deep learning with satellite & aerial imagery
$ npx skills add satellite-image-deep-learning/techniquesA fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.
$ npx skills add catboost/catboostH2O 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-3Open-source, low-code AutoML platform for Python. PyCaret 4.0: sklearn-native engine + React control plane.
$ npx skills add pycaret/pycaret🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.
$ npx skills add huggingface/transformersDeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
$ npx skills add deepspeedai/DeepSpeedHow 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 Graph Fraud Detection Papers 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.
Alternatives
Compare similar skills by workflow fit, trust score, quality, GitHub adoption, maintenance, and install readiness.
Current skill
A curated list of Graph/Transformer-based fraud, anomaly, and outlier detection papers & resources
A Python library for anomaly detection across tabular, time series, graph, text, and image data. 60+ detectors, benchmark-backed ADEngine orchestration, and an agentic workflow for AI agents.
$ npx skills add yzhao062/pyodA python library for user-friendly forecasting and anomaly detection on time series.
$ npx skills add unit8co/dartsA unified framework for machine learning with time series
$ npx skills add sktime/sktimeRay 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
$ npx skills add keras-team/keras💫 Industrial-strength Natural Language Processing (NLP) in Python
$ npx skills add explosion/spaCyThe AI developer platform. Use Weights & Biases to train and fine-tune models, and manage models from experimentation to production.
$ npx skills add wandb/wandbLow-code framework for building custom LLMs, neural networks, and other AI models
$ npx skills add ludwig-ai/ludwigFast and Accurate ML in 3 Lines of Code
$ npx skills add autogluon/autogluonTechniques for deep learning with satellite & aerial imagery
$ npx skills add satellite-image-deep-learning/techniquesA fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.
$ npx skills add catboost/catboostH2O 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-3Open-source, low-code AutoML platform for Python. PyCaret 4.0: sklearn-native engine + React control plane.
$ npx skills add pycaret/pycaret🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.
$ npx skills add huggingface/transformersDeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
$ npx skills add deepspeedai/DeepSpeedHow 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 Graph Fraud Detection Papers 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.