Job offersCompaniesTestsBlogI'm an employerSign upLog in
Home>IT Tests>Questions>Gradient descent is an optimization algorithm used to train neural networks. Its objective is to modify the model parameters until finding one of the cost function’s local minimum (<=> very efficient weights and bias values).

Question from the Deep learning - Fundamentals test

Gradient descent is an optimization algorithm used to train neural networks. Its objective is to modify the model parameters until finding one of the cost function’s local minimum (<=> very efficient weights and bias values).

Hard

Complete the sentence : Gradient descent is an optimization algorithm used to train neural networks. Its objective is to modify the model parameters until finding…

Author: MartinStatus: PublishedQuestion passed 175 times
Edit
0
Community EvaluationsNo one has reviewed this question yet, be the first!
Similar Questions
More questions about Deep learning
12
What is the relation between Artificial intelligence (AI), machine learning and deep learning?
8
What is the missing word in the following sentence: Overfitting is the production of a model that corresponds too closely to the training data set and may therefore fail to fit other data sets and so fail to perform any reliable forecast.
5
Given a neural network with 4 inputs, how many connections could exist between the input layer and the first hidden layer?
1
Which neural network type is the best for image processing?
1
In deep learning, the validation set is used to provide frequent and unbiased evaluations of the model’s fit on the training set while tuning its hyperparameters/parameters: in other words,the model is found and then tested on the validation set before to be improved once again.