ראיון עבודה machine learning

Which of the following is NOT supervised learning?

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מיין לפי

Suppose we would like to perform clustering on spatial data such as the geometrical locations of houses. We wish to produce clusters of many different sizes and shapes. Which of the following methods is the most appropriate?

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מיין לפי

The error function most suited for gradient descent using logistic regression is

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מיין לפי

Compared to the variance of the Maximum Likelihood Estimate (MLE), the variance of the Maximum A Posteriori (MAP) estimate is ___

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מיין לפי

___ refers to a model that can neither model the training data nor generalize to new data.

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מיין לפי

What does it mean to underfit your data model?

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מיין לפי

Asian user complains that your company's facial recognition model does not properly identify their facial expressions. What should you do?

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מיין לפי

You work for a website that helps match people up for lunch dates. The website boasts that it uses more than 500 predictors to find customers the perfect date, but many costumers complain that they get very few matches. What is a likely problem with your model?

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מיין לפי

(Mostly) whenever we see kernel visualizations online (or some other reference) we are actually seeing:

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מיין לפי

The activations for class A, B and C before softmax were 10,8 and 3. The different in softmax values for class A and class B would be :

1

מיין לפי

ראיון עבודה machine learning

Discuss, Learn and be Happy דיון בשאלות

Which of the following is NOT supervised learning?

Suppose we would like to perform clustering on spatial data such as the geometrical locations of houses. We wish to produce clusters of many different sizes and shapes. Which of the following methods is the most appropriate?

The error function most suited for gradient descent using logistic regression is

Compared to the variance of the Maximum Likelihood Estimate (MLE), the variance of the Maximum A Posteriori (MAP) estimate is ___

___ refers to a model that can neither model the training data nor generalize to new data.

What does it mean to underfit your data model?

Asian user complains that your company's facial recognition model does not properly identify their facial expressions. What should you do?

You work for a website that helps match people up for lunch dates. The website boasts that it uses more than 500 predictors to find customers the perfect date, but many costumers complain that they get very few matches. What is a likely problem with your model?

(Mostly) whenever we see kernel visualizations online (or some other reference) we are actually seeing:

The activations for class A, B and C before softmax were 10,8 and 3. The different in softmax values for class A and class B would be :