Skill 詳細

machine learning

Broad Python ML coverage from training through MLOps.

一致度直接一致機械学習 向けにレビュー済み
出典pluginagentmarketplace/custom-plugin-python外部ソース
報告インストール数318人気度の参考値

使用前に確認

自動レビューは関連性のみを確認し、安全性や推奨を保証しません。使用前に出典の説明を読んでください。

保存された出典プレビュー

SKILL.md

これはレビュー時に保存された抜粋です。完全で最新の内容は外部ソースを確認してください。

---
name: Machine Learning
description: Python machine learning with scikit-learn, PyTorch, and TensorFlow
version: "2.1.0"
sasmp_version: "1.3.0"
bonded_agent: 03-data-science
bond_type: PRIMARY_BOND

# Skill Configuration
retry_strategy: exponential_backoff
observability:
  logging: true
  metrics: model_accuracy
---

# Python Machine Learning Skill

## Overview
Build machine learning models using Python libraries including scikit-learn, PyTorch, and supporting tools.

## Topics Covered

### Scikit-learn
- Data preprocessing
- Model selection
- Training pipelines
- Cross-validation
- Hyperparameter tuning

### PyTorch Basics
- Tensor operations
- Neural network modules
- Training loops
- DataLoader usage
- GPU acceleration

### Feature Engineering
- Feature selection
- Dimensionality reduction
- Feature scaling
- Encoding techniques
- Missing data handling

### Model Evaluation
- Metrics selection
- Confusion matrix
- ROC curves
- Learning curves
- Model comparison

### MLOps Basics
- Model serialization
- Experiment tracking (MLflow)
- Model versioning
- Serving models
- Reproducibility

## Prerequisites
- Python fundamentals
- NumPy and Pandas
- Statistics basics

## Learning Outcomes
- Train ML models
- Evaluate model performance
- Build ML pipelines
- Deploy models to production
GitHub で全文を読む (外部ページ)
関連情報

関連する仕事