History of ML Modern Neural Networks

ByAdmin July 8, 2021

Week – 2 History of ML: Modern Neural Networks of Launching into Machine Learning

Dropout is a technique used to prevent a model from overfitting. Dropout works by randomly setting the outgoing edges of hidden units (neurons that make up hidden layers) to 0 at each update of the training phase.

Dropout is a technique used to prevent a model from underfitting. Dropout works by randomly setting the outgoing edges of hidden units (neurons that make up hidden layers) to 0 at each update of the training phase.

Dropout is a technique used to prevent a model from overfitting. Dropout works by randomly setting the outgoing edges of hidden units (neurons that make up hidden layers) to 1 at each update of the training phase.

None of the above

Dropout can help a model generalize by randomly setting the output for a given neuron to 0. In setting the output to 0, the cost function becomes more sensitive to neighbouring neurons changing the way the weights will be updated during the process of backpropagation.

Dropout can help a model generalize by randomly setting the output for a given neuron to 1. In setting the output to 1, the cost function becomes more sensitive to neighbouring neurons changing the way the weights will be updated during the process of backpropagation.

Both A and B

None of the above

Neural networks are a set of algorithms, modeled loosely after the human brain, that are designed to recognize patterns. They interpret sensory data through a kind of machine perception, labeling or clustering raw input. The patterns they recognize are numerical, contained in vectors, into which all real-world data, be it images, sound, text or time series, must be translated.

1 point

Neural networks are a set of algorithms, modeled loosely after the human brain, that are designed to recognize patterns.

Neural networks interpret sensory data through a kind of machine perception, labeling or clustering raw input.

The patterns neural networks recognize are numerical, contained in vectors, into which all real-world data, be it images, sound, text or time series, must be translated.

All of the above

Convolutional Neural Network

Modular Neural Network

Recurrent Neural Network

Sine Neural Network

Adding dropout layers. Dropout is a technique used to prevent a model from overfitting. Dropout works by randomly setting the outgoing edges of hidden units (neurons that make up hidden layers) to 0 at each update of the training phase.

Performing data augmentation, which is a technique to artificially create new training data from existing training data. This is done by applying domain-specific techniques to examples from the training data that create new and different training examples.

Adding noise – for example, adding Gaussian noise to input variables.

Gaussian noise, or white noise, has a mean of zero and a standard deviation of one and can be generated as needed using a pseudorandom number generator.

All of the above

Launching into Machine Learning

Week – 3 Lesson Quiz of Launching into Machine Learning

ByAdmin July 8, 2021

Week – 3 Lesson Quiz of Launching into Machine Learning 1. Fill in the blanks: At its core, a ________ is a method of evaluating how well your algorithm models…

Launching into Machine Learning

Practice Quiz on Improve Data Quality

ByAdmin July 8, 2021

Week – 1 Practice Quiz on Improve Data Quality of Launching into Machine Learning 1. Which of the following is not a Data Quality attribute? 1 point Consistency Accuracy Auditability…

Launching into Machine Learning

Supervised Learning

ByAdmin July 8, 2021

Week – 2 Supervised Learning of Launching into Machine Learning 1. Which of the following machine learning models have labels, or in other words, the correct answers to whatever it…

Launching into Machine Learning

Generalization and ML Models

ByAdmin July 8, 2021

Week – 4 Generalization and ML Models of Launching into Machine Learning 1. Question 1 Which is the best way to assess the quality of a model? 1 point Observing…

Launching into Machine Learning

Module Quiz of Launching into Machine Learning

ByAdmin July 8, 2021

Week – 3 Module Quiz of Launching into Machine Learning 1. What is the main difference between RMSE and MSE? 1 point The loss metric output for RMSE is measured…

Launching into Machine Learning

Decision Trees

ByAdmin July 8, 2021

Week – 2 Decision Trees of Launching into Machine Learning 1. Decision trees are one of the most intuitive machine learning algorithms. They can be used for which of the…

Week – 2 History of ML: Modern Neural Networks of Launching into Machine Learning

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