The person appears to be a/an East Asian Female, approximately 40 to 49 years old.
Here’s a simple Keras model that you can use:

```python
import tensorflow as tf

model = tf.keras.models.Sequential([
    tf.keras.layers.Input(shape=(5,)),
    tf.keras.layers.Dense(128, activation='relu'),
    tf.keras.layers.Dense(128, activation='relu'),
    tf.keras.layers.Dense(128, activation='relu'),
    tf.keras.layers.Dense(128, activation='relu'),
    tf.keras.layers.Dense(5, activation='linear')
])

model.compile(loss='mse', optimizer='Adam')
```
This model is structured to take in 5 features and output 5 predictions, which can be useful for various applications in data science and machine learning.
Here’s a simple Keras model that you can use: 

```python
import tensorflow as tf

model = tf.keras.models.Sequential([
    tf.keras.layers.Input(shape=(5,)),
    tf.keras.layers.Dense(128, activation='relu'),
    tf.keras.layers.Dense(128, activation='relu'),
    tf.keras.layers.Dense(128, activation='relu'),
    tf.keras.layers.Dense(128, activation='relu'),
    tf.keras.layers.Dense(5, activation='linear')
])

model.compile(loss='mse', optimizer='Adam')
```

This model consists of an input layer that accepts 5 features, followed by four hidden layers with 128 neurons each, and an output layer that produces 5 outputs. You can adjust the number of neurons and layers based on your specific needs.