machine-learning
1
deep-learning
Build and train neural networks with PyTorch - MLPs, CNNs, and training best practices
pluginagentmarketplace
data-ai
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machine-learning
1
ml-frameworks
ML framework best practices for PyTorch, TensorFlow, scikit-learn, and modern ML libraries including training patterns and optimization.
doanchienthangdev
data-ai
machine-learning
1
torch-geometric
Graph Neural Networks (PyG). Node/graph classification, link prediction, GCN, GAT, GraphSAGE, heterogeneous graphs, molecular property prediction, for geometric deep learning.
hxk622
data-ai
machine-learning
1
rust-candle-whisper
Implement native Rust ML inference with Candle framework. Use when building GPU-accelerated ML pipelines without Python dependencies.
gar-ai
data-ai
machine-learning
1
machine-learning
Supervised & unsupervised learning, scikit-learn, XGBoost, model evaluation, feature engineering for production ML
pluginagentmarketplace
data-ai
machine-learning
1
mastering-pytorch-rl-nlp
Expert guidance for PyTorch development covering Deep Reinforcement Learning and NLP Transformers. This skill provides comprehensive knowledge for building RL agents with TorchRL (DQN, PPO) and NLP systems with HuggingFace Transformers. Use this skill when working with PyTorch 2.7+, implementing reinforcement learning algorithms, fine-tuning transformer models, or deploying ML systems to production. Includes current best practices, verified library versions (Dec 2025), and warnings about deprecated APIs.
SpillwaveSolutions
data-ai
machine-learning
1
experimenting-edge
Optimizes AI models for edge deployment through quantization, lazy loading, and memory management. Use when deploying models to resource-constrained environments, mobile devices, or edge computing scenarios. Do not use for cloud deployment, model training, or data preprocessing.
Git-Fg
data-ai
machine-learning
1
model-development
Model development practices including model selection, training pipelines, hyperparameter tuning, evaluation, and model selection strategies.
doanchienthangdev
data-ai
machine-learning
1
finops-ai-expert
Cost optimization for AI workloads - model selection, GPU sizing, commitment strategies, and multi-cloud cost management
frankxai
data-ai
machine-learning
1
aeon
This skill should be used for time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search. Use when working with temporal data, sequential patterns, or time-indexed observations requiring specialized algorithms beyond standard ML approaches. Particularly suited for univariate and multivariate time series analysis with scikit-learn compatible APIs.
hxk622
data-ai
machine-learning
1
perform-sweep
Design, configure, launch, and analyze ablation sweeps for GRPO training. Use for hypothesis testing, hyperparameter experiments, and systematic comparisons.
bglick13
data-ai
machine-learning
1
pytorch-lightning
Deep learning framework (PyTorch Lightning). Organize PyTorch code into LightningModules, configure Trainers for multi-GPU/TPU, implement data pipelines, callbacks, logging (W&B, TensorBoard), distributed training (DDP, FSDP, DeepSpeed), for scalable neural network training.
hxk622
data-ai
machine-learning
1
mlops-basics
Master MLOps fundamentals - lifecycle, principles, tools, practices, and organizational adoption
pluginagentmarketplace
data-ai
machine-learning
1
stable-baselines3
Production-ready reinforcement learning algorithms (PPO, SAC, DQN, TD3, DDPG, A2C) with scikit-learn-like API. Use for standard RL experiments, quick prototyping, and well-documented algorithm implementations. Best for single-agent RL with Gymnasium environments. For high-performance parallel training, multi-agent systems, or custom vectorized environments, use pufferlib instead.
hxk622
data-ai
machine-learning
1
finops-ai-expert
Cost optimization for AI workloads - model selection, GPU sizing, commitment strategies, and multi-cloud cost management
frankxai
data-ai
machine-learning
1
deep-learning
PyTorch, TensorFlow, neural networks, CNNs, transformers, and deep learning for production
pluginagentmarketplace
data-ai
machine-learning
1
deep-learning-primer
Deep learning foundations including neural network basics, backpropagation, optimization, regularization, and training best practices.
doanchienthangdev
data-ai
machine-learning
1
nixtla-cross-validator
Performs rigorous time series cross-validation using expanding and sliding windows. Use when needing to evaluate the performance of time series models on unseen data. Trigger with cross validate time series, evaluate forecasting model, time series backtesting.
intent-solutions-io
data-ai
machine-learning
1
pufferlib
High-performance reinforcement learning framework optimized for speed and scale. Use when you need fast parallel training, vectorized environments, multi-agent systems, or integration with game environments (Atari, Procgen, NetHack). Achieves 2-10x speedups over standard implementations. For quick prototyping or standard algorithm implementations with extensive documentation, use stable-baselines3 instead.
hxk622
data-ai
machine-learning
1
computer-vision
Build computer vision solutions - image classification, object detection, and transfer learning
pluginagentmarketplace
data-ai
machine-learning
1
efficient-ai
Efficient AI techniques including model compression, quantization, pruning, knowledge distillation, and hardware-aware optimization for production systems.
doanchienthangdev
data-ai
machine-learning
1
mind-parameter-modification
Modify cognitive parameters and behavioral settings.
starwreckntx
data-ai