Info Edge Interview Questions and Answers

Contains around 40 aptitude questions that include CS fundamentals and also logical reasoning type and 2 coding questions of medium level

Q1. Peak element in array
Ans. 
Peak element in array is the element which is greater than or equal to its neighbors.
• Iterate through the array and check if the current element is greater than its neighbors.

• If the current element is greater than both neighbors, it is a peak element.

• If the current element is at the start or end of the array, only compare with one neighbor.
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Q1. Simple question like using map it can be solved easily
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Q2. Prime number to check
Ans. 
A prime number is a number greater than 1 that can only be divided by 1 and itself.
• A prime number is a number greater than 1.

• It can only be divided by 1 and itself.

• Examples: 2, 3, 5, 7, 11, 13, 17, 19, 23, 29
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Q1. Palindrome all methods you can think
Ans. 
Various methods to check if a string is a palindrome
• Reverse the string and compare with the original string

• Iterate through the string from both ends towards the middle

• Use a stack to push the characters of the string and then pop them to compare with the original string
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Q1. Concepts of Dropout during Test Time?
Ans. 
Dropout is a regularization technique used during training, but typically not applied during test time to ensure full model performance.
• Dropout randomly sets a fraction of input units to zero during training to prevent overfitting.

• During test time, dropout is usually turned off, allowing the full network to make predictions.

• This ensures that all neurons contribute to the output, providing a more accurate representation...read more
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Q2. How Random Forest Solves the Problem of Overfitting?
Ans. 
Random Forest mitigates overfitting by averaging multiple decision trees, enhancing generalization and robustness.
• Ensemble Learning: Combines predictions from multiple trees to reduce variance.

• Bootstrap Aggregating: Each tree is trained on a random subset of data, promoting diversity.

• Feature Randomness: Randomly selects features for splitting, preventing dominance of any single feature.

• Example: In a dataset with noise,...read more
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Q3. Suppose you have very high imbalance problem, how and which Model will you choose to report?
Ans. 
For high imbalance problems, choose models like Random Forest or XGBoost, and use techniques like SMOTE for better performance.
• Use ensemble methods like Random Forest or Gradient Boosting (e.g., XGBoost) for better handling of imbalanced data.

• Consider using resampling techniques such as SMOTE (Synthetic Minority Over-sampling Technique) to balance the dataset.

• Evaluate models using metrics like F1-score, precision, reca...read more
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Q4. Deep Concepts of Transformers?
Ans. 
Transformers are advanced neural network architectures that excel in processing sequential data, particularly in NLP tasks.
• Self-Attention Mechanism: Allows the model to weigh the importance of different words in a sentence, e.g., in 'The cat sat on the mat', 'cat' and 'sat' are closely related.

• Positional Encoding: Since transformers don't have a built-in sense of order, positional encodings are added to input embedding...read more
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Q5. What is query, Key and Value pairs in self attention?
Ans. 
Query, Key, and Value are components of self-attention mechanisms in neural networks, enabling context-aware representations.
• In self-attention, each input element is transformed into three vectors: Query, Key, and Value.

• The Query vector represents the current element's focus, while the Key vector represents the context of other elements.

• The attention score is computed by taking the dot product of the Query and Key vect...read more
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Q6. How does Self Attention Works?
Ans. 
Self-attention allows models to weigh the importance of different words in a sequence when processing them, enhancing context understanding.
• Self-attention computes a weighted representation of input sequences, focusing on relevant parts.

• It uses three vectors: Query (Q), Key (K), and Value (V) to determine attention scores.

• For each word, the model calculates how much attention to pay to every other word in the sequence.

• ...read more
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Q7. Real Time Problems based on Multi Head Attention and it's use cases?
Ans. 
Multi-head attention enhances model performance by focusing on different parts of input data simultaneously.
• Improves natural language processing tasks like translation and summarization.

• Used in image processing for tasks like object detection and segmentation.

• Facilitates recommendation systems by analyzing user preferences from multiple perspectives.

• Enhances speech recognition by focusing on different phonetic features...read more
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Q8. Degree of Freedom, Chi Square Distribution?
Ans. 
Degrees of freedom in Chi-Square distribution indicate the number of independent values in a statistical calculation.
• Degrees of freedom (df) = number of categories - 1 in Chi-Square tests.

• Example: For a test with 5 categories, df = 5 - 1 = 4.

• In goodness-of-fit tests, df helps determine the critical value for hypothesis testing.

• Higher degrees of freedom lead to a more accurate approximation of the Chi-Square distributio...read more
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Q9. What is the mathematical framework behind Linear Regression? Real Time problem case.
Ans. 
Linear Regression uses statistical methods to model the relationship between variables, predicting outcomes based on input features.
• Linear regression assumes a linear relationship between the dependent and independent variables.

• The model can be represented as: Y = β0 + β1X1 + β2X2 + ... + βnXn + ε, where Y is the dependent variable.

• The coefficients (β) are estimated using the least squares method, minimizing the sum of...read more
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Q10. How are LLN and CLT are related?
Ans. 
LLN and CLT are statistical theorems that describe the behavior of sample averages as sample size increases.
• LLN (Law of Large Numbers) states that as the sample size increases, the sample mean converges to the population mean.

• CLT (Central Limit Theorem) states that the distribution of the sample mean approaches a normal distribution as sample size increases, regardless of the population's distribution.

• Both theorems are...read more
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Q11. Difference between Covariance and correlation?
Ans. 
Covariance measures the directional relationship between two variables, while correlation quantifies the strength and direction of that relationship.
• Covariance can take any value between -∞ and +∞, while correlation ranges from -1 to +1.

• Positive covariance indicates that two variables move in the same direction, while negative covariance indicates they move in opposite directions.

• Correlation standardizes covariance, ma...read more
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Q12. What are the assumptions underlying Linear Regression?
Ans. 
Linear regression relies on several key assumptions for valid results, including linearity, independence, and homoscedasticity.
• Linearity: The relationship between the independent and dependent variables should be linear. For example, predicting weight based on height.

• Independence: Observations should be independent of each other. For instance, data collected from different individuals should not influence each other.

• Ho...read more
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Normal fill in the bkanks

Q1. Basic questions
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Q2. Introduction about yourself and go through your experience.
Ans. 
I am a dedicated and experienced professional with a background in marketing and project management.
• Over 5 years of experience in marketing and project management roles

• Successfully led multiple marketing campaigns resulting in increased brand awareness

• Managed cross-functional teams to deliver projects on time and within budget

• Strong analytical and problem-solving skills

• Proficient in data analysis and reporting tools su...read more
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Q1. Can you introduce yourself and explain why you are interested in this operational role?
Ans. 
Detail-oriented analyst with a passion for optimizing operations and enhancing efficiency in dynamic environments.
• Background in data analysis and process improvement, demonstrated through my previous role at XYZ Corp where I reduced operational costs by 15%.

• Strong analytical skills, evidenced by my ability to interpret complex datasets and provide actionable insights that drive decision-making.

• Experience in cross-funct...read more
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Q2. What are some questions related to Excel functions such as VLOOKUP, HLOOKUP, and Pivot Tables?
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Q3. Some SQL queries like joins and window function
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Q1. What you know about this company Why you choose the this role
Ans. 
This company is a leader in data management solutions, known for its commitment to accuracy and efficiency in data entry services.
• The company has a strong reputation for providing high-quality data entry services, which aligns with my attention to detail.

• I admire the company's innovative approach to technology, which enhances data processing efficiency.

• The role of Data Entry Operator is crucial for maintaining data int...read more
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Q2. Do you know about company
Ans. 
The company specializes in data management solutions, providing efficient services to enhance productivity and accuracy in data entry tasks.
• Founded in 2010, the company has over a decade of experience in the data entry industry.

• They offer a range of services including data processing, data cleansing, and data conversion.

• The company utilizes advanced software tools to ensure high accuracy and efficiency in data entry ta...read more
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Q3. You know about company of experience of role
Ans. 
I have experience in data entry roles, focusing on accuracy, efficiency, and data management in various industries.
• Proficient in using data entry software like Microsoft Excel and Google Sheets.

• Maintained a 99% accuracy rate in entering patient records at a healthcare facility.

• Managed large datasets, ensuring timely updates and data integrity.

• Experience in handling sensitive information while adhering to confidentialit...read more
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Basic questions only.

Q1. Basic questions like, how react works?
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Q2. What is the equivalent of ReactDOM in mobile application development?
Ans. 
The equivalent of ReactDOM in mobile application development is React Native.
• React Native is a framework for building mobile applications using React.

• It allows developers to write code in JavaScript and render native components.

• Just like ReactDOM in web development, React Native handles rendering components to the screen.
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It includes verbal quants and logical

It was generalized topic on ev and traditional vehicles

Q1. Experience and projects
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Q2. About database system
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Q3. About sql queries
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Q1. Why we hire you
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Q2. Tell me which is not in your resume
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