GAIN Credit Linux Administrator Interview Questions and Answers

Q1. Questions about your experience
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Q2. It will depend your experience
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You will be given a dataset and a questionnaire to be solved over it

Q1. Explain confidance interval
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Confidence interval is a range of values that is likely to contain the true population parameter with a certain level of confidence.
• Confidence interval is used to estimate the population parameter based on a sample statistic.

• It is calculated by taking the sample mean and adding or subtracting the margin of error.

• The level of confidence is typically set at 95% or 99%.

• For example, a 95% confidence interval for the averag...read more
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Q2. Explain logistic regression
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Logistic regression is a statistical method used to analyze and model the relationship between a binary dependent variable and one or more independent variables.
• It is used to predict the probability of a binary outcome (0 or 1).

• It uses a sigmoid function to map the input values to the output probability.

• It is commonly used in machine learning for classification problems.

• Example: predicting whether a customer will buy a...read more
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Q3. Use of confusion matrix
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Confusion matrix is a table used to evaluate the performance of a classification model.
• It helps in calculating various metrics like accuracy, precision, recall, F1 score, etc.

• It compares the predicted values with the actual values to identify true positives, true negatives, false positives, and false negatives.

• It is commonly used in machine learning and data science to evaluate the performance of classification models.

• ...read more
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Q4. Explain academic projects
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Academic projects are assignments given to students to apply their theoretical knowledge in practical scenarios.
• Academic projects are designed to help students gain hands-on experience in their field of study.

• They require students to apply their theoretical knowledge to solve real-world problems.

• Examples of academic projects include building a website, designing a software application, conducting a research study, or c...read more
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Q1. What do you know about crif
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Q2. What do you want to learn here
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Java 8, Mysql, sprin, c, c++

Q1. Questions based on core java and oops concepts
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Statistics assignment on given dataset

Q1. Credit Risk, loan disbursement process, PD model , machine learning
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Q1. Basics of Logistic regression
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Q2. What is Logistic Regression? What is Recall
Ans. 
Logistic Regression is a statistical method used to model the probability of a certain event occurring based on one or more predictor variables. Recall is a metric used to evaluate the performance of a classification model.
• Logistic Regression is used for binary classification tasks, where the outcome variable is categorical and has two classes.

• It estimates the probability that a given input belongs to a certain categor...read more
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Q3. What is Recall?
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Recall is a metric used in classification models to measure the ability of the model to find all relevant cases within a dataset.
• Recall is calculated as the number of true positive predictions divided by the sum of true positive and false negative predictions.

• It is also known as sensitivity or true positive rate.

• A high recall indicates that the model is good at identifying all relevant cases, even if it means more fals...read more
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Q4. What is the difference between linear and logistic reg.?
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Linear regression is used for predicting continuous values, while logistic regression is used for predicting binary outcomes.
• Linear regression is used when the target variable is continuous and has a linear relationship with the independent variables.

• Logistic regression is used when the target variable is binary or categorical and the relationship between independent variables and the target is non-linear.

• Linear regres...read more
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Q5. What are the performance metrics of Regression
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Performance metrics of Regression include Mean Squared Error, R-squared, Mean Absolute Error, etc.
• Mean Squared Error (MSE)

• R-squared (R^2)

• Mean Absolute Error (MAE)

• Root Mean Squared Error (RMSE)

• Adjusted R-squared
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Q1. Java basics questions and java basic answers waste interview maximum element in an array array merged opps concepts basic puzzels.
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Q2. Opps concepts basic programs
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