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Scale data\\n2. Choose method\\n3. Transform\\n4. Visualize\n\n## Tools Used\nsklearn\n\n## Examples\n```python\nfrom src.skills.data_science.dimensionality_reduction import Skill\n\nskill = Skill()\nresult = await skill.run(SkillInput(data={\"key\": \"value\"}))\n```\n\n## Best Practices\nStandardize features before PCA\n","# Dimensionality Reduction\n\n## Description\nReduce feature space using PCA or t-SNE\n\n## When to Use\nWhen dealing with high-dimensional data\n\n## Workflow\n1. Scale data\\n2. Choose method\\n3. Transform\\n4. Visualize\n\n## Tools Used\nsklearn\n\n## Examples\n```python\nfrom src.skills.data_science.dimensionality_reduction import Skill\n\nskill = Skill()\nresult = await skill.run(SkillInput(data={\"key\": \"value\"}))\n```\n\n## Best Practices\nStandardize features before PCA\n",{"name":5,"description":7},"main","19d5aed8a5e48ff5443f425990d1df390d792bee","src\u002Fskills\u002Fdata_science\u002Fdimensionality_reduction","https:\u002F\u002Fgithub.com\u002Fsadjad6\u002Fopen-autonomous-research-lab","https:\u002F\u002Fgithub.com\u002Fsadjad6","https:\u002F\u002Fsadeghi-ai.de\u002F","AI\u002FML Engineer | GenAI, RAG & Agentic AI | MLOps & ML Systems | PhD in Physics. 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