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Found 8 Skills
Expert guidance for data analysis, visualization, and Jupyter Notebook development with pandas, matplotlib, seaborn, and numpy.
Guidelines for data analysis and Jupyter Notebook development with pandas, matplotlib, seaborn, and numpy.
Data analysis best practices with pandas, numpy, matplotlib, seaborn, and Jupyter notebooks.
Deploy the Cortex CLASSIFY_TEXT tutorial notebook to the user's Snowflake account and provide a link to open it in Snowsight. Use when user wants to learn text classification through a Jupyter notebook experience.
Python data analysis with pandas, numpy, and analytics libraries
Use when implementing data analysis pipelines, statistical tests, or bioinformatics workflows in code (Python/R), particularly for genomics, transcriptomics, proteomics, or other -omics data.
Generates a Jupyter notebook that evaluates a fine-tuned SageMaker model using LLM-as-a-Judge. Use when the user says "evaluate my model", "how did my model perform", "compare models", or after a training job completes. Supports built-in and custom evaluation metrics, evaluation dataset setup, and judge model selection.
Generates a Jupyter notebook that transforms datasets between ML schemas for model training or evaluation. Use when the user says "transform", "convert", "reformat", "change the format", or when a dataset's schema needs to change to match the target format — always use this skill for format changes rather than writing inline transformation code. Supports OpenAI chat, SageMaker SFT/DPO/RLVR, HuggingFace preference, Bedrock Nova, VERL, and custom JSONL formats from local files or S3.