Encoding categorical data is a crucial step in data preprocessing. By converting categorical data into a numeric format, machine learning models can interpret and work more effectively.

Their work demonstrates that quantum circuits for data encoding in quantum machine learning can be greatly simplified without compromising accuracy or robustness. The research was published Sept ...

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One of the key obstacles to efficient quantum machine learning has been encoding classical data into quantum states, a computationally challenging task requiring deeply entangled circuits.