How to do it...

This section walks through the steps to predict gender based on height and weight.

1. Create a Python function called input_normalize to input new values for height and weight and output a normalized height and weight, as seen in the following script:

def input_normalize(height, weight):
    inputHeight = (height - x_mean[0])/x_std[0]
    inputWeight = (weight - x_mean[1])/x_std[1]
    return inputHeight, inputWeight

2. Assign a variable called score to the function for the values of 70 inches for the height and 180 lbs for the weight, as seen in the following script:

score = input_normalize(70, 180)

3. Create another Python function, called predict_gender, to output a probability score, gender_score, between 0 and 1, as well as a gender description, by applying the summation with w1, w2, and b as well as the sigmoid function, as seen in the following script:

def predict_gender(raw_score):
    gender_summation = raw_score[0]*w1 + raw_score[1]*w2 + b
    gender_score = sigmoid(gender_summation)
    if gender_score <= 0.5:
        gender = 'Female'
    else:
        gender = 'Male'
    return gender, gender_score