Define Data Pipeline. Explain the Key Stages of AI Data Pipeline. PDF

 An AI Data Pipeline is a process that collects, cleans, transforms, stores, and delivers data for Artificial Intelligence systems.

First, data is collected from different sources. Then the data is cleaned and transformed into a suitable format. After that, the processed data is stored and used to train AI models.

Finally, the AI system analyzes data and gives predictions or decisions.

In simple words, an AI Data Pipeline is the complete journey of data from collection to AI prediction.

Define Data Pipeline. Explain the Key Stages of AI Data Pipeline.

    The AI Data Pipeline refers to the systematic process through which raw data is collected, processed, and transformed into a trained Artificial Intelligence model.

    It ensures that data is properly prepared before being used for machine learning or deep learning applications.

    Each stage in the pipeline plays a crucial role in improving model performance and accuracy.

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