Shaadi.com Interview Questions, Process, and Tips

Q1. Find deepest object in nested object
Ans. 
Use recursion to find the deepest object in a nested object structure.
• Use recursion to iterate through each key in the object

• Keep track of the depth level as you traverse the object

• Compare the depth levels of each nested object to find the deepest one
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Q2. Explain ACID Properties
Ans. 
ACID properties are a set of principles that guarantee reliability and consistency in database transactions.
• Atomicity ensures that all operations in a transaction are completed successfully or none at all.

• Consistency ensures that the database remains in a valid state before and after the transaction.

• Isolation ensures that transactions are executed independently without interference from other transactions.

• Durability en...read more
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Q1. Personal career-related questions
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Q2. Professional experience related questions
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Q1. Describe product management
Ans. 
Product management involves overseeing the development and marketing of a product from conception to launch.
• Identifying market needs and opportunities

• Defining product strategy and roadmap

• Collaborating with cross-functional teams

• Prioritizing features and enhancements

• Analyzing data and feedback for product improvements
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Q1. Rca question on product
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The assessment consists of a dataset for which we are required to build a machine learning model and submit the results along with code and detailed documentation

Q1. What are ensemble models
Ans. 
Ensemble models are machine learning models that combine multiple individual models to improve predictive performance.
• Ensemble models work by aggregating predictions from multiple models to make a final prediction.

• Common types of ensemble models include Random Forest, Gradient Boosting, and AdaBoost.

• Ensemble models are often more accurate and robust than individual models.

• They can reduce overfitting and increase genera...read more
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Q2. Difference between bagging and boosting
Ans. 
Bagging and boosting are ensemble learning techniques used to improve the performance of machine learning models by combining multiple weak learners.
• Bagging (Bootstrap Aggregating) involves training multiple models independently on different subsets of the training data and then combining their predictions through averaging or voting.

• Boosting involves training multiple models sequentially, where each subsequent model c...read more
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Q3. A lot of tree based questions
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Q1. Impliment counter using closure in js
Ans. 
Implement a counter using closure in JavaScript.
• Create a function that returns another function which increments a counter variable.

• The counter variable should be defined in the outer function's scope and only accessible to the inner function.

• Each time the inner function is called, increment the counter variable and return its value.
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Q2. Explain promises, promise.all(), impliment binary search
Ans. 
Promises are objects representing the eventual completion or failure of an asynchronous operation. promise.all() is a method that takes an array of promises and returns a single promise that resolves when all of the promises have resolved.
• Promises are used in JavaScript to handle asynchronous operations.

• promise.all() takes an array of promises and returns a single promise that resolves when all promises in the array ha...read more
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Q1. Questions on kafka, cache invalidation, diff b/w authentication and authorization
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