Statistics ChallengeIn the Python file, you will be creating a model to predict the age of abalone's from a subset of the abalone dataset which we proide in CSV format. Part of the program is already implemented, your goal is to set up the model, train the model on the training data set, and print out some results.These are the following details you need to implement:First you'll convert the feature dataset into a numpy array.Then you should create a Sequential model with 2 layers. The first layer should be a Dense layer with 64 units, and the second layer should also be a Dense one with units set to 1.Once the model is set up, you should compile it with a MeanSquaredError() loss and the optimizer set to optimizers.Adam().Then, when you fit the dataset on abalone_features and abalone_features, make sure to set the following values: epochs=10, verbose=0.Finally, you should print both the history from fitting the model, and the model summary.
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Statistics ChallengeIn the Python file, you will be creating a model to predict the age of abalone's from a subset of the abalone dataset which we proide in CSV format. Part of the program is already implemented, your goal is to set up the model, train the model on the training data set, and print out some results.These are the following details you need to implement:First you'll convert the feature dataset into a numpy array.Then you should create a Sequential model with 2 layers. The first layer should be a Dense layer with 64 units, and the second layer should also be a Dense one with units set to 1.Once the model is set up, you should compile it with a MeanSquaredError() loss and the optimizer set to optimizers.Adam().Then, when you fit the dataset on abalone_features and abalone_features, make sure to set the following values: epochs=10, verbose=0.Finally, you should print both the history from fitting the model, and the model summary.
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First you'll convert the feature dataset into a numpy array.Then you should create a Sequential model with 2 layers. The first layer should be a Dense layer with 64 units, and the second layer should also be a Dense one with units set to 1.Once the model is set up, you should compile it with a MeanSquaredError() loss and the optimizer set to optimizers.Adam().Then, when you fit the dataset on abalone_features and abalone_features, make sure to set the following values: epochs=10, verbose=0.Finally, you should print both the history from fitting the model, and the model summary.
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