开发编程
#python
machine-learning
Python machine learning with scikit-learn, PyTorch, and TensorFlow
DeepseekModel
官方收录技能
质量 优秀 · 90
v1.0.0
获取
https://deepseekmodel.com/api/download.php?id=midudev-autoskills-packages-autoskills-skills-registry-machine-learning-skill-md&format=skill
下载 .skill
标准格式，含 system_prompt 与 model_config，导入任意 Agent 框架即可使用
.skill 文件中 system_prompt 字段的实际内容。
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 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
Agent 识别该技能的关键词，点击任意一个即可复制。
该技能未提供触发词。
下载的 .skill 包内含以下字段。
| 字段 | 说明 |
|---|---|
| format | 格式标识（skill/v1） |
| skill_id | 技能唯一 ID |
| name | 技能名称 |
| version | 版本号 |
| description | 技能描述 |
| category | 所属分类（数组） |
| trigger_words | 触发词列表 |
| tags | 标签列表 |
| source | 来源标识 |
| source_url | 来源链接（本页地址） |
| exported_at | 导出时间（每次下载生成） |
| system_prompt | 系统提示词正文 |
| model_config | 模型参数：provider / model / temperature / max_tokens / top_p |
| examples | 示例 |
| install_guide | 各平台导入说明（Coze / Dify / Claude / 自定义框架） |
