ITC's Agri Business Division Interview Questions and Answers

Correlation measures the strength and direction of a linear relationship between two variables, while covariance measures the extent to which two variables change together.

• Correlation ranges from -1 to 1, where 1 indicates a perfect positive relationship, -1 indicates a perfect negative relationship, and 0 indicates no relationship.

• Covariance can be positive, negative, or zero. A positive covariance indicates that as one variable increases, the other variable also tends to in...read more

Decision tree is a tree-like model of decisions and their possible consequences, while random forest is an ensemble learning method that builds multiple decision trees and merges them together.

• Decision tree is a flowchart-like structure where each internal node represents a decision based on an attribute, each branch represents the outcome of the decision, and each leaf node represents a class label.

• Random forest is a collection of decision trees trained on random subsets of ...read more

Linear regression is a statistical method used to model the relationship between a dependent variable and one or more independent variables.

• Linear regression is used to predict the value of a dependent variable based on the value of one or more independent variables.

• It assumes a linear relationship between the independent and dependent variables.

• The goal of linear regression is to find the best-fitting line that minimizes the sum of squared differences between the observed an...read more

Random forest is an ensemble learning method used for classification and regression tasks.

• Random forest is a collection of decision trees that are trained on random subsets of the data.

• Each tree in the random forest independently predicts the target variable, and the final prediction is made by averaging the predictions of all trees.

• Random forest is robust to overfitting and noisy data, and it can handle large datasets with high dimensionality.

• Random forest can be used for bo...read more

XGBoost is an optimized distributed gradient boosting library designed for efficient and accurate large-scale machine learning.

• XGBoost stands for eXtreme Gradient Boosting.

• It is a popular machine learning algorithm known for its speed and performance.

• XGBoost is used for regression, classification, ranking, and user-defined prediction problems.

• It is based on the gradient boosting framework and uses decision trees as base learners.

• XGBoost has implementations in various programm...read more

LSTM and GRU are types of recurrent neural networks used for processing sequential data.

• LSTM (Long Short-Term Memory) networks are capable of learning long-term dependencies in data.

• GRU (Gated Recurrent Unit) networks are simpler than LSTM and have fewer parameters.

• LSTM has three gates (input, output, forget) while GRU has two gates (update, reset).

• LSTM is better at capturing long-term dependencies but is more complex, while GRU is simpler and faster to train.

• Both LSTM and GR...read more