3. Deep Learning and Variants_Session 3 _20240121 - Neural Network Training and Inventory Management Quiz

What is the purpose of training a network in deep learning?

To minimize the cost function by updating network parameters

How are the weights adjusted in deep learning networks during training?

Weights are decreased for high outputs

What is Gradient Descent used for in deep learning?

To move towards the gradient of the cost function

What is the purpose of the learning rate in Gradient Descent?

To scale down the gradient to control the step size Signup and view all the answers

How are weights adjusted if the output in deep learning is too low?

Increase the weights attached to high inputs Signup and view all the answers

What does the cost function aim to achieve in a neural network?

Minimize the error between predicted and actual output Signup and view all the answers

What is the mini-batch size recommended for large data sets?

64-512 Signup and view all the answers

Which feature represents the amount of product in transit from the source?

in_transit_qty Signup and view all the answers

What does 'went_on_backorder' represent in the context of inventory management?

Product actually went on backorder Signup and view all the answers

What risk flag is associated with 'Part risk flag stop_auto_buy'?

stop_auto_buy Signup and view all the answers

Which feature provides the forecast sales for the next 6 months?

forecast_6_month Signup and view all the answers

What is the purpose of 'perf_12_month_avg' in inventory management?

Source performance for prior 12 month period Signup and view all the answers

What is the abbreviation for 'Backward propagation of Errors' in the context of ANN learning?

BPROP Signup and view all the answers

In the context of updating weights in neural networks, what does '𝛼' represent?

Learning rate Signup and view all the answers

What does Full Batch training involve in the context of machine learning algorithms?

Using the entire dataset to train and update weights Signup and view all the answers

What distinguishes Stochastic Gradient Descent from batch or mini-batch gradient descent?

Updating weights with each individual sample Signup and view all the answers

How is an 'epoch' defined in the context of mini-batch gradient descent?

Completing all mini-batches once Signup and view all the answers

For a dataset with less than 2000 samples, which type of gradient descent is recommended?

Batch Signup and view all the answers

How many hidden layers are typically needed to handle most structured-data problems?

1 hidden layer Signup and view all the answers

What is the best way to determine the number of neurons in a neural network according to the text?

Experiment and use cross-validation Signup and view all the answers

In terms of network topology for neural networks, what is considered rare according to the text?

Having more than two hidden layers Signup and view all the answers

For unstructured data like images and text, which machine learning method is typically NOT suitable as mentioned in the text?

Regression models Signup and view all the answers

When comparing different machine learning methods, which method is suitable for both structured and unstructured data according to the text?

Neural Networks Signup and view all the answers

Which type of data requires a large number of training samples according to the text?

Structured data Signup and view all the answers