Skills
Browse curated AI skills for development, design, testing, and more.
Showing 1-12 of 12
Hugging Face Model Trainer
@sickn33
Low Risk
Train or fine-tune TRL language models on Hugging Face Jobs, including SFT, DPO, GRPO, and GGUF export.
Deploymentfine-tuning
Fda Medtech Compliance Auditor
@sickn33
Low Risk
Expert AI auditor for Medical Device (SaMD) compliance, IEC 62304, and 21 CFR Part 820. Reviews DHFs, technical files, and software validation.
fine-tuning
4.6
Data Scientist
@sickn33
Low Risk
Expert data scientist for advanced analytics, machine learning, and statistical modeling. Handles complex data analysis, predictive modeling, and business intelligence.
Deploymentfine-tuning
Hugging Face Vision Trainer
@sickn33
Low Risk
Train or fine-tune vision models on Hugging Face Jobs for detection, classification, and SAM or SAM2 segmentation.
fine-tuning
4.4290
ML Pipeline Workflow
@sickn33
Low Risk
Complete end-to-end MLOps pipeline orchestration from data preparation through model deployment.
Deploymentfine-tuning
Azure AI ML Py
@sickn33
Low Risk
Azure Machine Learning SDK v2 for Python. Use for ML workspaces, jobs, models, datasets, compute, and pipelines.
Azurefine-tuning
Puzzle Activity Planner
@sickn33
Low Risk
Plan puzzle-based activities for classrooms, parties, and events with pre-configured generator links
fine-tuning
4.6262
Updated May 25, 2026
Pytorch Patterns
@affaan-m
Low Risk
PyTorch deep learning patterns and best practices for building robust, efficient, and reproducible training pipelines, model architectures, and data loading.
fine-tuning
4.3240
Updated May 25, 2026Hugging Face Trackio
@sickn33
Low Risk
Track ML experiments with Trackio using Python logging, alerts, and CLI metric retrieval.
fine-tuning
4.8186
Updated May 25, 2026Mle Workflow
@affaan-m
Low Risk
Production machine-learning engineering workflow for data contracts, reproducible training, model evaluation, deployment, monitoring, and rollback. Use when building, reviewing, or hardening ML systems beyond one-off notebooks.
fine-tuning
4.4456
Updated May 25, 2026ML Engineer
@sickn33
Low Risk
Build production ML systems with PyTorch 2.x, TensorFlow, and modern ML frameworks. Implements model serving, feature engineering, A/B testing, and monitoring.
Azurefine-tuning
ML Pipeline
@Jeffallan
Safe
Designs and implements production-grade ML pipeline infrastructure: configures experiment tracking with MLflow or Weights & Biases, creates Kubeflow or Airflow DAGs for training orchestration, builds feature store schemas with Feast, deploys model registries, and automates retraining and validation
infrastructuremachine-learning