10+ GenC Next Interview Questions and Answers for Freshers

Calculate minimum steps for a Knight to reach target position on a chessboard.

• Use BFS algorithm to find shortest path from Knight's starting position to target position.

• Consider all possible moves of the Knight on the chessboard.

• Keep track of visited positions to avoid revisiting them.

• Return the minimum number of moves required for the Knight to reach the target position.

The task is to find the total number of ways to make change for a specified value using given denominations.

• Create a dynamic programming table to store the number of ways to make change for each value up to the target value.

• Iterate through each denomination and update the table accordingly.

• The final answer will be the value in the table at the target value.

• Consider edge cases like when the target value is 0 or when there are no denominations that can make the change.

• Example: ...read more

Sort an array of positive integers (0, 1, 2) in non-decreasing order.

• Iterate through the array and count the occurrences of 0, 1, and 2.

• Update the array with the counts of each element in non-decreasing order.

• Print the sorted array for each test case.

Bounding methods in React are used to limit the scope of a component's updates.

• Bounding methods include shouldComponentUpdate, getSnapshotBeforeUpdate, and componentDidUpdate.

• shouldComponentUpdate allows a component to decide if it should update based on changes in props or state.

• getSnapshotBeforeUpdate allows a component to capture information before a change is made to the DOM.

• componentDidUpdate is called after a component updates and can be used to perform additional actio...read more

Regularization techniques are used to prevent overfitting in machine learning models.

• L1 regularization (Lasso)

• L2 regularization (Ridge)

• Elastic Net regularization

• Dropout regularization

• Early stopping

• Data augmentation

• Batch normalization

Creating a machine learning model involves data preparation, model selection, training, evaluation, and deployment.

• Data preparation involves cleaning, transforming, and splitting the data into training and testing sets.

• Model selection involves choosing the appropriate algorithm and hyperparameters for the problem.

• Training the model involves feeding the training data to the algorithm and adjusting the parameters to minimize the error.

• Evaluation involves testing the model on th...read more

Program to perform Merge sort on an array of N numbers.

• Divide the array into two halves recursively

• Sort the two halves using merge sort

• Merge the two sorted halves

• Repeat until the entire array is sorted

• Time complexity: O(nlogn)

Gradient descent is an optimization algorithm used to minimize the cost function of a machine learning model.

• Start with an initial guess for the model parameters

• Calculate the gradient of the cost function with respect to each parameter

• Update the parameters in the opposite direction of the gradient

• Repeat until convergence or a maximum number of iterations is reached

My favorite technology is artificial intelligence.

• AI has the potential to revolutionize various industries

• It can automate repetitive tasks and improve efficiency

• AI can also help in making better decisions by analyzing large amounts of data

• Examples include chatbots, image recognition, and predictive analytics

Poison distribution refers to the spread of toxic substances through various means.

• Poison distribution can occur through intentional or accidental means.

• Examples include the distribution of poison through food or water, or the release of toxic chemicals into the environment.

• Poison distribution can have serious health consequences and may require immediate medical attention.

• Prevention measures such as proper storage and disposal of toxic substances can help prevent poison dist...read more

PCA stands for Principal Component Analysis. It is a statistical technique used for dimensionality reduction.

• PCA is used to identify patterns in data and reduce the number of variables in a dataset.

• It works by transforming the original variables into a new set of variables called principal components.

• These principal components are ordered by the amount of variance they explain in the data.

• PCA is commonly used in fields such as finance, biology, and image processing.

• Example: P...read more

Clustering algorithm groups similar data points together based on their characteristics.

• Clustering is an unsupervised learning technique.

• It can be used for customer segmentation, image segmentation, etc.

• K-means, hierarchical clustering, and DBSCAN are popular clustering algorithms.

• The choice of algorithm depends on the data and the problem at hand.