Technical Interview Questions
SVM algorithms have basically advantages in terms of complexity. First I would like to clear that both Logistic regression as well as SVM can form non linear decision surfaces and can be coupled with the kernel trick. If Logistic regression can be coupled with kernel then why use SVM? ● SVM is found to have … Read more
Collinearity is a linear association between two predictors. Multicollinearity is a situation where two or more predictors are highly linearly related. Collinearity and multicollinearity are concepts related to the correlation among independent variables in a regression model: Collinearity: Definition: Collinearity refers to the linear relationship between two independent variables in a regression model. Scenario: It … Read more
The information gain is based on the decrease in entropy after a dataset is split on an attribute. Constructing a decision tree is all about finding the attribute that returns the highest information gain (i.e., the most homogeneous branches). Step 1: Calculate entropy of the target. In the context of machine learning and decision trees, … Read more
Understand the business model: Try to understand the related attributes for the spam mail Data acquisitions: Collect the spam mail to read the hidden pattern from them Data cleaning: Clean the unstructured or semi structured data Exploratory data analysis: Use statistical concepts to understand the data like spread, outlier, etc. Use machine learning algorithms to … Read more
To build a model in machine learning, you need to follow few steps: Understand the business model Data acquisitions Data cleaning Exploratory data analysis Use machine learning algorithms to make a model Use unknown dataset to check the accuracy of the model The three main stages of building a model in machine learning are: Data … Read more