Tekion Lead Engineer Interview Questions and Answers

Fancy string problem

Q1. You are given 2 tables, customer and orders, you have to write an SQL query to fetch the total order placed by each customer and also give the total order amount.
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Q2. Java Streams question to find the total number of employees that have salary greater than 50000
Ans. 
Use Java Streams to find total employees with salary > 50000
• Filter employees with salary > 50000 using stream.filter()

• Count the number of employees using stream.count()
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Q3. The various annotations used in Springboot @Entity, @RestController etc
Ans. 
Annotations in Springboot like @Entity, @RestController are used for defining classes and endpoints respectively.
• Annotations like @Entity are used to define JPA entities in Springboot.

• Annotations like @RestController are used to define RESTful web services endpoints.

• Annotations like @Autowired are used for dependency injection in Springboot.
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Q4. AWS services used in my previous project
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In my previous project, I used AWS services such as EC2, S3, and RDS for hosting, storage, and database management.
• EC2 for hosting application servers

• S3 for storing and retrieving files

• RDS for managing relational databases
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Q1. All questions were asked based on my resume. So prepare well from your resume.
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Q1. 4th round was a one on one with the manager, asked me general questions about why I was looking for a job change.
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Q1. Transaction in Spring Boot
Ans. 
Transactions in Spring Boot help manage database operations as a single unit of work.
• Transactions ensure ACID properties (Atomicity, Consistency, Isolation, Durability) for database operations.

• Use @Transactional annotation to mark a method as transactional.

• Transactions can be managed programmatically using TransactionTemplate.

• Rollback can be triggered manually in case of exceptions.

• Spring Boot supports both declarative
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Q2. Java Array and problem solving
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Aptitude Test online

Q1. Machine learning
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Q2. Data science, statistics
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Q1. Salary discussion
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Q1. Our project contains interview question related to JAVA.
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Q1. Train a Decision Tree based on dataset provided?
Ans. 
Train a Decision Tree based on provided dataset.
• Preprocess the dataset by handling missing values and encoding categorical variables.

• Split the dataset into training and testing sets.

• Train the Decision Tree model on the training set.

• Evaluate the model's performance on the testing set using metrics like accuracy or F1 score.
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Q2. How can you do feature selection?
Ans. 
Feature selection can be done using techniques like filter methods, wrapper methods, and embedded methods.
• Filter methods involve selecting features based on statistical measures like correlation, chi-squared test, etc.

• Wrapper methods use a specific machine learning algorithm to evaluate the importance of features through iterative selection.

• Embedded methods incorporate feature selection within the model training proces...read more
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Q1. Questions were mostly around system design, you will be given a case like a stock system and specific use case is asked to design end to end from UI to backend.
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Q2. Some of the system debugging/performance improvement questions are asked from both UI and backend.
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You can get the information and answer in Google

Q1. Xg boost, naive Bayes algorithm, standard deviation formula and detailed information about that
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Q2. What is xg boost All about naive Bayes algorithm Standard deviations and the formula
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Q3. What is the Byes rules and there in deep
Ans. 
Bayes' rule is a fundamental concept in probability theory that allows us to update our beliefs based on new evidence.
• Bayes' rule is named after Thomas Bayes, an 18th-century mathematician.

• It is also known as Bayes' theorem or Bayes' law.

• Bayes' rule calculates the probability of an event based on prior knowledge and new evidence.

• It is commonly used in machine learning and statistical inference.

• The formula for Bayes' ru...read more
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