Webstep Technologies Interview Questions and Answers for Experienced

Q1. Debugging Techniques, Types of Logs
Ans. 
Debugging techniques involve using logs to identify and fix issues in code.
• Types of logs include console logs, file logs, event logs, and trace logs.

• Debugging techniques include using breakpoints, stepping through code, and analyzing error messages.

• Logging frameworks like log4net and NLog can be used to generate logs for debugging purposes.
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Q2. Aptitude type questions
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Q3. Basic sql queries, sql injection
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Q4. Sessions and cookies
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Q1. What is difference between random forest and xgboost
Ans. 
Random forest is an ensemble learning method using decision trees, while XGBoost is a gradient boosting algorithm.
• Random forest builds multiple decision trees and combines their predictions, while XGBoost builds trees sequentially to correct errors.

• Random forest is less prone to overfitting compared to XGBoost.

• XGBoost is computationally efficient and often outperforms random forest in terms of predictive accuracy.

• Rando...read more
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Q2. What is your project problem statement
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Q3. How you convince for clients the model is useful, what are the matrix
Ans. 
I convince clients of model usefulness by showcasing its accuracy, precision, recall, and F1 score.
• Explain the model's accuracy in predicting outcomes compared to actual results

• Discuss precision - the proportion of true positive predictions out of all positive predictions

• Highlight recall - the proportion of true positive predictions out of all actual positives

• Mention F1 score - the balance between precision and recall,
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Q1. How you take data from client
Ans. 
I collect data from clients through various methods such as surveys, interviews, API integrations, and data sharing agreements.
• Conduct surveys to gather specific data points from clients

• Interview clients to understand their data needs and preferences

• Integrate with client's systems through APIs to access real-time data

• Establish data sharing agreements to receive data from clients securely
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Q2. What are hyper parameters you turned for your model
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Tuned hyperparameters include learning rate, batch size, number of layers, and activation functions.
• Adjusted learning rate to improve model convergence

• Optimized batch size for better training efficiency

• Experimented with different numbers of layers to find optimal model complexity

• Tried various activation functions to enhance model performance
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Q3. What difference model you use in your project
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Q4. How you work with llm
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Q5. What are the features in your data set
Ans. 
The features in the data set include age, gender, income, education level, location, and purchase history.
• Age

• Gender

• Income

• Education level

• Location

• Purchase history
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Q6. What feature engineering you did in project
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2 section
MCQ + CODING(intermediate level)

Q1. Basic questions related to JS, ANGULAR, Node JS, and some Coding questions
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Todo application was the assignment task to complete in one day.

Q1. What is your name
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Q2. What is my name
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Q1. What is hr name
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Q2. What is company name
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Q3. What is company hobbies
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Q4. What is company circular activity
Ans. 
Company circular activity is a team-building exercise or event organized by a company to promote collaboration and communication among employees.
• It is usually a planned activity outside of regular work hours.

• It can include activities such as team sports, group outings, workshops, or volunteer work.

• The goal is to strengthen relationships, boost morale, and improve teamwork within the company.

• Examples: company picnic, te
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Q1. Round 1 Technical Questions on Node.Js and Angular 1. Difference between shallow clone and deep clone. 2. 1 question to test skill on object from abv topic. 3. What r Promises? Types? 4. Difference betwee...read more
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Q1. Experience with microservices? questions on kafka and queue system How to handle payment failure?
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Q1. C# related questions
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Q2. Database related questions
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Q1. What is bias variance tradeoff in machine learning
Ans. 
Bias-variance tradeoff is the balance between underfitting and overfitting in machine learning models.
• Bias refers to error from erroneous assumptions in the learning algorithm, leading to underfitting.

• Variance refers to error from sensitivity to small fluctuations in the training set, leading to overfitting.

• The tradeoff involves finding the right level of model complexity to minimize both bias and variance.

• Regularizati...read more
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Q2. Explain your project
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Q3. Write a SQL code to find 2nd highest salary
Ans. 
SQL code to find 2nd highest salary
• Use the MAX() function to find the highest salary

• Use the WHERE clause to exclude the highest salary

• Order the salaries in descending order and limit the result to 1
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Q1. Asked mostly hadoop cluster questions
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Asked to build a stage cluster