Best machine learning skills for Claude Code, Codex and other agents.

Machine learning in Python with scikit-learn. An agent skill from zLanqing/codex-claude-academic-skills.

zLanqing/codex-claude-academic-skills

Runs lm-evaluation-harness to benchmark language models on academic suites such as MMLU, GSM8K and HumanEval, compare models and track training checkpoints.

Orchestra-Research/AI-Research-SKILLs

Explains machine learning, LLMs, AI agents and speech modeling in a Hung-Yi Lee-inspired teaching style, drawing on a knowledge base built from his lectures and research references.

voidful/hung-yi-lee-skill

Evaluate and improve GenAI models and agents using the Google GenAI Evaluation SDK.

GoogleCloudPlatform/vertex-ai-samples

World-class data science skill for statistical modeling, experimentation, causal inference, and advanced analytics.

Raidriar7170/hermes-skilleval

Trains and evaluates several WiFi-signal-based pose and sensing models, from unsupervised pose estimation to domain adaptation and publishing.

ruvnet/RuView

Takes a Kaggle competition from rules and validation design through baselines, ensembling and notebook architecture to a scored submission.

FrankS-IntelLab/agentic-kaggle-skill

Plans memory headroom, works through out-of-memory failures and watches temperature and power during long ML training jobs on NVIDIA DGX Spark.

wshobson/agents

Analyze user retention and churn using survival analysis, cohort analysis, and machine learning.

liangdabiao/claude-data-analysis-ultra-main

Reference patterns for writing qiskit 2.x code for variational quantum machine learning: feature maps, VQC training, VQE for chemistry, MPS circuits and noise models.

aiming-lab/AutoResearchClaw

Scaffold a brand-new Comet example in this repo from the canonical template under templates/integration-example/.

comet-ml/comet-examples

Designs ML pipeline infrastructure: experiment tracking with MLflow or Weights & Biases, Kubeflow and Airflow orchestration, Feast feature stores and model validation gates.

Jeffallan/claude-skills

Routes agents to the right tangermeme reference for analyzing trained genomic deep learning models, from attributions and motif experiments to variant effects and design.

jmschrei/tangermeme

Shows how to organize PyTorch training with Lightning's LightningModule and Trainer, covering validation, DDP, callbacks and learning-rate scheduling.

Orchestra-Research/AI-Research-SKILLs

Working knowledge of the geoML Python package (github.com/italo-goncalves/geoML): variational Gaussian processes for spatial data, implicit geological modelling, block models, drillhole data…

italo-goncalves/geoML

A skill your agent uses when building or auditing a radiomics or tabular clinical-ML prediction model with a classical learner (LASSO, SVM, random forest, XGBoost and similar).

Aperivue/medsci-skills

Turns a plain-language model training request into a validated QuantMind training config file that can be imported from the Model Training page.

qusong0627/QuantMind

A standardized CLI wrapper for Uni-Mol molecular ML workflows that handles representation extraction (embeddings), model training (regression/classification), and property prediction with built-in…

jinzhezenggroup/computational-chemistry-agent-skills

A skill your agent uses when the user wants to evolve an ML model/program through population-based search rather than a single sequential refine loop — a generational evolution where parallel…

gaasher/Agent-Loop-Skills

Guides an agent through tracking ML experiments with W&B: run logging, config capture, hyperparameter sweeps, artifacts and a model registry.

Orchestra-Research/AI-Research-SKILLs

Build a new time-series analytics use case on top of the deployed Time Series Analytics microservice — bring it up with Docker Compose (from a repo clone, or by fetching the compose files from…

open-edge-platform/edge-ai-libraries

A skill your agent uses for GPU-accelerated machine learning on tabular data using NVIDIA cuML.

wahyudesu/Fastapi-AI-Production-Template

Entry point and controller for computational chemistry and materials workflows.

JCLiuGroup/AI-Computational-Chemist

Estimate a covariance / correlation / precision matrix incrementally with precise.

microprediction/precise

Serverless GPU cloud platform for running ML workloads. An agent skill from Orchestra-Research/AI-Research-SKILLs.

Orchestra-Research/AI-Research-SKILLs

Keeps a persistent, append-only journal of ML experiment hypotheses and results across sessions, so no hyperparameter or architecture change runs without being logged first.

Leeroo-AI/superml

Generate model metadata for an ML model so it works with xybrid.

xybrid-ai/xybrid

Invoke ML models, run vector search, and connect to MCP servers from Databricks Apps.

databricks-solutions/databricks-apps-cookbook

CEO checks consistency of agent outputs during post-completion review

chekusu/wanman

Produces ranked, evidence-grounded next steps when an ML experiment has stalled, drawing on a Leeroopedia knowledge base or on fetched docs and issues.

Leeroo-AI/superml

Uses Ray Data to read, transform and write large datasets across a cluster for ML training and batch inference, with streaming execution and optional GPU steps.

Orchestra-Research/AI-Research-SKILLs

Scales PyTorch, TensorFlow and Hugging Face training from a single GPU to multi-node clusters with Ray Train, including Ray Tune sweeps and checkpoint recovery.

Orchestra-Research/AI-Research-SKILLs

Run LAMMPS molecular dynamics with DeePMD-kit machine learning potentials.

Hello-QM/catgo-LRG

Guides time series machine learning with the aeon toolkit: classification, regression, clustering, forecasting, anomaly detection, segmentation and similarity search.

davila7/claude-code-templates

Applies the reasoning, principles, and frameworks of Andrew Ng (machine learning pioneer, co-founder of Coursera and DeepLearning.AI, Stanford University, and former Google Brain lead).

K-Dense-AI/mimeo

Online (incremental) covariance, correlation, and precision estimation in Python — the streaming complement to sklearn.covariance.

microprediction/precise

Declare the pipeline from data source to predictor as a skrub DataOps graph.

probabl-ai/skills

Guides an agent through designing an MLOps pipeline that covers data preparation, training, validation and deployment, with DAG orchestration and reference guides.

wshobson/agents

Core ML, Create ML, Vision framework, Natural Language framework, on-device ML integration.

gustavscirulis/snapgrid

Works with genomic intervals using gtars, a Rust toolkit with Python bindings: overlap detection, coverage tracks, tokenization for ML models and reference sequences.

davila7/claude-code-templates

Computational pathology toolkit for analyzing whole-slide images (WSI) and multiparametric imaging data.

davila7/claude-code-templates

Builds machine learning pipelines on clinical data with PyHealth: EHR datasets, prediction tasks, medical code mapping, healthcare models and evaluation.

davila7/claude-code-templates

Fits and evaluates survival models with scikit-survival: Cox models, Random Survival Forests, boosting, survival SVMs, concordance index, Brier score and competing risks.

davila7/claude-code-templates

Explains machine learning predictions with SHAP: picking the right explainer, computing Shapley values and drawing waterfall, beeswarm, bar and force plots.

davila7/claude-code-templates

Molecular machine learning toolkit. An agent skill from davila7/claude-code-templates.

davila7/claude-code-templates

Add new AI models to Kiln's mlmodellist.py and produce a Discord announcement.

Kiln-AI/Kiln

Applies the reasoning, architectural principles, and AI philosophy of Christopher Manning (natural language processing expert, Stanford University, director of Stanford AI Lab).

K-Dense-AI/mimeo

Perform comprehensive regression analysis and predictive modeling using linear regression, decision trees, and random forests.

liangdabiao/claude-data-analysis-ultra-main