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cache Interview Questions Part1

Multiple choice questions on Javascript

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The basic purpose of the toLocaleString() is to _________

__________ aids in identifying associations, correlations, and frequent patterns in data.

Cassandra Interview Questions Part

__________ step of KDD process helps in identifying valuable patterns.

Classification problems aid in predicting __________ outputs.

The following are tools offered by deepnet platforms, except __________.

Which of the following strategies have higher control on sites/pages getting listed in Google SERPs?

In Master-Slave databases, all writes are written to the ____________.

What do you think Go is a case sensitive language?

__________statistics provides the summary statistics of the data.

Identify the correct statement in the following in secure programming questions


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How are the parameters updated during Gradient Descent process? View:-13028
Question Posted on 06 Jul 2020

How are the parameters updated during Gradient Descent process?
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Which of the following option/options are the advantages of SQLite? View:-1161
Question Posted on 05 Jul 2020

Which of the following option/options are the advantages of SQLite?
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What measures the extent to which the predictions change between various realizations of the model? View:-8868
Question Posted on 05 Jul 2020

What measures the extent to which the predictions change between various realizations of the model?
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____________ function is used as a mapping function for classification problems. View:-9171
Question Posted on 11 Jul 2020

____________ function is used as a mapping function for classification problems.
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I have a scenario where my hypothesis fits my training set well but fails to generalize for the test set. View:-14002
Question Posted on 09 Jul 2020

I have a scenario where my hypothesis fits my training set well but fails to generalize for the test set.
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For an overfit data set, the cross-validation error will be much bigger than the training error. View:-0
Question Posted on 08 Jul 2020

For an overfit data set, the cross-validation error will be much bigger than the training error.
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____________ controls the magnitude of a step taken during Gradient Descent. View:-10116
Question Posted on 13 Jul 2020

____________ controls the magnitude of a step taken during Gradient Descent.
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When an ML Model has a high bias, getting more training data will help in improving the model. View:-9834
Question Posted on 12 Jul 2020

When an ML Model has a high bias, getting more training data will help in improving the model.
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What is the Learning Technique in which the right answer is given for each example in the data called? View:-7242
Question Posted on 10 Jul 2020

What is the Learning Technique in which the right answer is given for each example in the data called?
Ch....
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For ____________, the error is determined by getting the proportion of values misclassified by the model. View:-15365
Question Posted on 10 Jul 2020

For ____________, the error is determined by getting the proportion of values misclassified by the model.
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For ____________, the error is calculated by finding the sum of squared distance between actual and predicted values. View:-15694
Question Posted on 10 Jul 2020

For ____________, the error is calculated by finding the sum of squared distance between actual and predicted....
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What is the range of the output values for a sigmoid function? View:-10686
Question Posted on 08 Jul 2020

What is the range of the output values for a sigmoid function?
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____________ measures how far the predictions are from the actual values. View:-8561
Question Posted on 07 Jul 2020

____________ measures how far the predictions are from the actual values.
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What is the name of the function that takes the input and maps it to the output variable called? View:-10291
Question Posted on 07 Jul 2020

What is the name of the function that takes the input and maps it to the output variable called?
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____________ is the line that separates y = 0 and y = 1 in a logistic function. View:-19875
Question Posted on 07 Jul 2020

____________ is the line that separates y = 0 and y = 1 in a logistic function.
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