AutoAI is a Python-based framework that automates regression and classification tasks on numerical data. It excels in model search, hyper-parameter tuning, and generates high-quality Jupyter Notebook code, making it a powerful tool for data scientists and ML practitioners.
claude install blobcity/autoaiAutoAI is a Python-based framework that automates regression and classification tasks on numerical data. It excels in model search, hyper-parameter tuning, and generates high-quality Jupyter Notebook code, making it a powerful tool for data scientists and ML practitioners.
Automating model selection for predictive analytics
Hyper-parameter tuning for improved model performance
Generating reproducible Jupyter Notebooks for data analysis
claude install blobcity/autoaigit clone https://github.com/blobcity/autoaiCopy the install command above and run it in your terminal.
Launch Claude Code, Cursor, or your preferred AI coding agent.
Use the prompt template or examples below to test the skill.
Adapt the skill to your specific use case and workflow.
Using AutoAI, analyze the [DATASET] to identify key patterns and trends. Perform regression or classification tasks as appropriate. Generate a Jupyter Notebook with the complete code and visualizations. Optimize the model using hyper-parameter tuning and provide a summary of the findings.
After analyzing the 'Customer Churn Dataset' using AutoAI, the framework identified several key patterns. The model search process evaluated multiple algorithms and selected Random Forest as the best fit for this classification task. Hyper-parameter tuning improved the model's accuracy to 87%. The generated Jupyter Notebook includes detailed code for data preprocessing, model training, and evaluation. Key findings indicate that contract length and monthly charges are the most significant predictors of customer churn. The notebook also provides visualizations such as feature importance plots and confusion matrices to support these insights.
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