“machine learning”

Use for GPU-accelerated machine learning on tabular data using NVIDIA cuML.

Expert knowledge for Azure Machine Learning development including troubleshooting, best practices, decision making, architecture & design patterns, limits &…

Applies Tom M.

Explain trained machine learning models through feature attribution, local explanations, and behavior summaries.

LQF Machine Learning Expert Guide - Routed skill for ML/Statistical Modeling with Critical Discussion Mode.

Evaluate trained machine learning models with the right metrics and comparison logic.

Master ML operations best practices in Arabic

Research contribution advancing agent and reasoning capabilities through novel approaches to model development, training, and evaluation.

Best practices for scikit-learn machine learning, model development, evaluation, and deployment in Python

Machine learning in Python with scikit-learn.

Supports machine learning in Python with scikit-learn.

Machine learning with scikit-learn.

Apple HIG guidance for Apple technology integrations: Siri, Apple Pay, HealthKit, HomeKit, ARKit, machine learning, generative AI, iCloud, Sign in with Apple…

Fine-tune MACE machine learning interatomic potentials on custom datasets.

Fine-tune MatGL machine learning interatomic potentials on custom datasets.

Detects and prevents data leakage in machine learning and mathematical modeling.

Fine-tune Fairchem machine learning interatomic potentials (UMA, ESEN) on custom datasets.

Leverages BigQuery's built-in machine learning and GenAI capabilities for advanced data analytics.

Benchmark of inference speed of Machine Learning Interatomic Potentials (MLIPs).

Azure Machine Learning SDK v2 for Python.

Explain and audit machine-learning predictions with SHAP.

Train a property predictor head on top of a Machine Learning Interatomic Potential (MLIP) backbone (MACE or MatGL) to predict custom intensive or extensive…

AI and machine learning workflow covering LLM application development, RAG implementation, agent architecture, ML pipelines, and AI-powered features.

Builds and validates PyHealth clinical machine-learning pipelines for EHR, signals, imaging, and medical codes.