Multiple Linear Regression Model by using Tensorflow

The feature normalization should be done by subtracting mean and dividing by range (or standard deviation).

def feature_normalize(train_X):

    global mean, std
    mean = np.mean(train_X, axis=0)
    std = np.std(train_X, axis=0)

    return (train_X - mean) / std

Do not forget to normalize your features when you make this prediction.

predict_X = (predict_X - mean)/std