9/20/2023 0 Comments No man sky missing vector code![]() abalone_model = tf.keras.Sequential([Ībalone_pile(loss = tf.(), Since there is only a single input tensor, a tf.keras.Sequential model is sufficient here. Next make a regression model predict the age. Pack the features into a single NumPy array.: abalone_features = np.array(abalone_features)Īrray(, ![]() The nominal task for this dataset is to predict the age from the other measurements, so separate the features and labels for training: abalone_features = abalone_py()Ībalone_labels = abalone_features.pop('Age')įor this dataset you will treat all features identically. “Abalone shell” (by Nicki Dugan Pogue, CC BY-SA 2.0) ![]() The dataset contains a set of measurements of abalone, a type of sea snail. "Viscera weight", "Shell weight", "Age"]) Names=["Length", "Diameter", "Height", "Whole weight", "Shucked weight", Here is how to download the data into a pandas DataFrame: abalone_train = pd.read_csv(
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