18 Questions
In the given code snippet, what library is used for creating a deep neural network?
TensorFlow
What is the purpose of using 'epochs' in a neural network model?
To define the number of training iterations on the dataset
Which method is used to split the dataset into training and testing sets in the given code?
train_test_split()
What type of loss function is specified in the model compilation in the code snippet?
'mean_squared_error'
What metric is commonly used to evaluate the performance of a regression model like the one in the code snippet?
Mean Squared Error
What is the purpose of using 'StandardScaler' in the provided code snippet?
To perform feature scaling on input data
What is the purpose of the 'epochs' setting in the given TensorFlow code snippet?
To set the number of times the entire dataset will pass through the model
What does the 'linear_regression' function in the code snippet aim to achieve?
Minimize the mean squared error between predicted and true values
Which function is used to compute the mean squared error in the given TensorFlow code snippet?
tf.reduce_mean(tf.square(y_true-y_pred))
What is the purpose of 'optimizer.apply_gradients(zip(gradients,[w,b]))' in the given code snippet?
To update the weights and biases based on computed gradients
In deep learning, what does the 'model loss' refer to?
The difference between predicted and true labels during training
What is the function of 'model.compile(optimizer='adam', loss='mean_squared_error', metrics=['accuracy'])' in the given TensorFlow code snippet?
To compile and specify the optimizer, loss function, and evaluation metrics for the model
What is the purpose of setting the 'random_state' parameter in train_test_split?
To ensure reproducibility by initializing a random seed for the data splitting process
What is the purpose of using 'StandardScaler' in this code snippet?
To scale the input features to have a mean of 0 and a variance of 1
Why is 'softmax' activation used in the output layer of the neural network model?
To obtain class probabilities for multi-class classification
What does 'model.compile(optimizer='adam', loss='mse', metrics=['accuracy'])' specify in this code snippet?
Adam optimizer, mean squared error loss function, and accuracy as the metric for model evaluation
What does 'model.fit(X_train, y_train, epochs=50, batch_size=6, validation_split=0.1)' indicate?
Training the model on X_train with y_train labels for 50 epochs using a batch size of 6 and 10% validation split
What does 'print(f"Final training accuracy: {history.history['accuracy'][-1]}")' display?
The final training accuracy achieved by the neural network model
Learn how to use TensorFlow and Scikit-Learn to work with the Linnerud dataset, including data loading, preprocessing, and model evaluation. This quiz covers topics such as data splitting, feature scaling, and performance metrics like classification report and confusion matrix.
Make Your Own Quizzes and Flashcards
Convert your notes into interactive study material.
Get started for free
