Programming, Artificial Intelligence, Machine Learning, Data Science, Python.
transformation x = np.dot(x, W1) + b1 # Apply ReLU activation x = relu(x) # Second layer transformation x = np.dot(x, W2) + b2 return x # Applying the FFN to each concatenated vector ffn_outputs = np.array([apply_ffn(person, W1, b1, W2, b2) for person in concatenated_results]) # Print the outputs