How can the evaluation of character strings to numerical values be optimized for accurate neural network training in PHP?

When evaluating character strings to numerical values for neural network training in PHP, it is important to preprocess the data to ensure accurate training. One way to optimize this process is by using techniques such as one-hot encoding or word embedding to convert the characters into numerical values that can be easily understood by the neural network. This will help improve the performance and accuracy of the neural network during training.

// Example code snippet for one-hot encoding character strings
function oneHotEncode($string, $vocab_size) {
    $encoded = array_fill(0, $vocab_size, 0);
    $chars = str_split($string);
    
    foreach($chars as $char) {
        $index = ord($char);
        $encoded[$index] = 1;
    }
    
    return $encoded;
}

// Example of how to use one-hot encoding
$string = "hello";
$vocab_size = 128; // ASCII characters
$encoded_string = oneHotEncode($string, $vocab_size);
print_r($encoded_string);