Automated ML with PyCaret

PyCaret Overview:

PyCaret is an open-source machine learning library in Python designed to simplify the machine learning workflow. It automates complex processes, allowing you to replace hundreds of lines of code with just a few. PyCaret integrates several machine learning libraries like scikit-learn, XGBoost, and LightGBM to streamline tasks.

PyCaret Workflow:

1. Setup:

   • Prepares the data for modeling by handling preprocessing tasks such as missing value imputation, encoding categorical variables, and feature scaling.

2. Compare Models:

   • PyCaret automatically trains and evaluates multiple models to identify the best-performing one based on a selected metric.

3. Analyze Model:

   • Visualize the model's performance through various interactive visualizations, helping to finalize the model for production.

4. Prediction:

   • The selected model is used to predict target values on both test and unseen datasets.

5. Save:

   • Save the trained model for future use or deployment.

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For a comprehensive step-by-step guide, including dataset exploration and code execution, please refer to the complete walkthrough videos playlist available on YouTube.

Playlist: YouTube Walkthrough Videos