This page represents a list of **questions** which can be used for preparation of **machine learning interviews**. Here is the link to first set of machine learning interview questions as part of this series. The following are some of the areas covered in this set of questions:

- Univariate vs Multivariate linear regression
- Supervised vs unsupervised learning
- Algorithms such as KNN, K-means, SVM etc.

#### Which of the following type of cost function is used for univariate linear expression?

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Wrong!

#### The hypothesis function such as f(x) = mx + c where x is an variable and c is a constant, is an example of which of the following?

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Wrong!

#### The hypothesis function such as f(x) = m1x1 + m2x2 + c where x1, and x2 are variables and c is a constant, is an example of which of the following?

Correct!
Wrong!

#### For gradient descent to converge quickly, it is recommended to make sure features are on similar scale

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#### PCA, KPCA, ICA are related with which of the following?

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#### SVM can only be used to solve classification problems?

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#### Perceptron in machine learning is used for _______?

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#### Logistic regression models are examples of which of the following?

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#### KNN is _________ algorithm?

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Wrong!

#### K-means is _________ algorithm?

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Wrong!

Introduction to Machine Learning Set 2

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