You're developing a custom TensorFlow gcp video

Full Certification Question

You're developing a custom TensorFlow classification model based on tabular data stored in BigQuery. The dataset comprises hundreds of millions of rows with both categorical and numerical features. Your goal is to use a MaxMin scaler on some numerical features and apply one-hot encoding to categorical features like SKU names. The model will be trained over multiple epochs, and you aim to minimize both effort and cost. What approach should you take?