“machine learning”

Computer Science fundamentals — Machine Learning, NLP, Computer Vision, Algorithms, Cryptography, Static Analysis, and Theoretical CS.

Runs a machine-learning experiment that can be trusted.

This skill should be used for time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection…

This project is an AI-powered aimbot that uses machine learning models to detect and aim at targets in games through screen capture analysis.

This project is an AI-powered FPS aimbot that uses computer vision and machine learning to detect and aim at enemy players in first-person shooter games.

Featurizes molecules for machine learning with molfeat — ECFP/MACCS/MAP4 fingerprints, RDKit and Mordred physicochemical descriptors, pharmacophore and shape…

Interactive visual curriculum teaching foundational Machine Learning & Data Science concepts (Naive-Bayes, Confusion Matrix & PR trade-offs, Differential…

An overview of the core model API of SeisBench, a Python framework for training and applying machine learning algorithms to seismic data.

Automated hyperparameter optimization for machine learning models using Optuna or scikit-learn search.

Use DeepXDE for scientific machine learning, PINNs, DeepONet/operator learning, backend selection, training, and troubleshooting.

Use DeepChem for molecular machine learning, data loading, featurization, model training, MoleculeNet, docking, and optional backend troubleshooting.

Generate and engineer features from raw tabular data for machine learning.

Master machine learning foundations - algorithms, preprocessing, feature engineering, and evaluation

Compatibility route for older GNOS learning invocations; continue through learning-orchestrator.

High-performance numerical computing and machine learning workflows using JAX.

Pharmaceutical machine-learning workflow guide for library profiling, molecular featurization, benchmark dataset fetch, medicinal-chemistry filtering, and…

Runs molecular machine learning with DeepChem — diverse featurizers, pre-built MoleculeNet benchmark datasets, and pre-trained models (ChemBERTa, GROVER) for…

Implement Amazon Macie to automatically discover, classify, and protect sensitive data in S3 buckets using machine learning and pattern matching for PII…

Safely reproduce and audit machine learning paper results with full traceability.

Hygiene for machine-learning training runs and comparisons — what to save while a run is in flight, how to keep runs from overwriting each other, and what…

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

把课题拆成连续学习文章，并根据用户反馈调整后续深度、角度和节奏。用户要求系统学习一个主题、继续下一篇或按反馈调整课程时使用。

Comprehensive geospatial science skill covering 70+ topics in remote sensing, GIS, spatial analysis, and machine learning for Earth observation.

Comprehensive geospatial science skill covering remote sensing, GIS, spatial analysis, machine learning for earth observation, and 30+ scientific domains.