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AI is more than GenAI
Practical AI: Machine Learning, Data Science, LLM
Iterate to Innovate: Fine-Tuning Data Transformation
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Data transformation processes can be implemented in various ways, even through simplistic methods such as analyzing pixel values to categorize images. A basic approach might involve setting a threshold percentage of red pixels to determine if an image contains a cat. However, hardcoding parameter values lacks accuracy and flexibility. Instead, developers can adopt iterative techniques to explore various parameter settings systematically, leveraging a dataset of example inputs and outputs. This approach allows for optimizing parameters to achieve higher accuracy in labeling, thus enhancing the effectiveness of the data transformation process.
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