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10+ TCS Interview Questions and Answers

Updated 22 Jan 2025

Q1. Can you describe your current project or any past projects that are related to machine learning?

Ans.

Developed a machine learning model to predict customer churn for a telecom company.

  • Used supervised learning techniques such as logistic regression and random forests

  • Preprocessed data by handling missing values and encoding categorical variables

  • Evaluated model performance using metrics like accuracy, precision, and recall

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Q2. Common metrics to find accuracy of linnear regression model and Logistic regression model?

Ans.

Common metrics for linear and logistic regression models are R-squared and confusion matrix respectively.

  • For linear regression model, common metric is R-squared which measures the proportion of the variance in the dependent variable that is predictable from the independent variables.

  • For logistic regression model, common metric is confusion matrix which includes metrics like accuracy, precision, recall, and F1 score to evaluate the performance of the model.

  • Accuracy is the prop...read more

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Q3. Diff betn random forest vs decision tree algorithm?

Ans.

Random forest is an ensemble learning method that uses multiple decision trees to make predictions.

  • Random forest is a collection of decision trees that are trained on different subsets of the data.

  • Decision tree is a single tree-like structure that makes decisions based on features of the data.

  • Random forest reduces overfitting by averaging the predictions of multiple trees.

  • Decision tree can be prone to overfitting if not pruned properly.

  • Random forest is more robust and accurat...read more

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Q4. How insurance will help common people?

Ans.

Insurance provides financial protection and peace of mind to common people in case of unexpected events.

  • Insurance helps common people by providing financial protection against unexpected events such as accidents, illnesses, and natural disasters.

  • It also provides peace of mind by reducing the financial burden and stress that comes with such events.

  • Insurance can also help common people plan for their future by providing retirement and investment options.

  • For example, health insu...read more

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Q5. Tell me example of ensemble technique?

Ans.

Ensemble technique combines multiple models to improve prediction accuracy.

  • Ensemble methods include bagging, boosting, and stacking

  • Random Forest is an example of ensemble technique using bagging

  • Gradient Boosting Machine (GBM) is an example of ensemble technique using boosting

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Q6. Diff betn linnear and logistic regression?

Ans.

Linear regression is used for continuous variables while logistic regression is used for binary classification.

  • Linear regression predicts continuous values while logistic regression predicts probabilities.

  • Linear regression uses a linear equation to model the relationship between the independent and dependent variables.

  • Logistic regression uses the logistic function to model the probability of a binary outcome.

  • Linear regression is used for tasks like predicting house prices bas...read more

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Q7. What is Linnear regression ?

Ans.

Linear regression is a statistical method used to model the relationship between a dependent variable and one or more independent variables.

  • Linear regression aims to find the best-fitting straight line that describes the relationship between variables.

  • It is commonly used for prediction and forecasting in various fields such as finance, economics, and social sciences.

  • The equation for linear regression is typically represented as y = mx + b, where y is the dependent variable, x...read more

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Q8. What is recall and F1?

Ans.

Recall is the ratio of correctly predicted positive observations to the all observations in actual class. F1 is the harmonic mean of precision and recall.

  • Recall is calculated as TP / (TP + FN)

  • F1 score is calculated as 2 * (precision * recall) / (precision + recall)

  • Recall is important in scenarios where false negatives are costly, like in medical diagnosis

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Q9. How you can achieve the target ?

Ans.

I can achieve the target by setting clear goals, creating a plan, and consistently tracking progress.

  • Set specific and measurable goals

  • Create a detailed plan with actionable steps

  • Track progress regularly and make adjustments as needed

  • Stay motivated and focused on the end result

  • Collaborate with team members and seek feedback

  • Continuously learn and improve skills

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Q10. How you create client relation ?

Ans.

I create client relations by building trust, providing excellent service, and maintaining open communication.

  • Listen actively to clients' needs and concerns

  • Respond promptly to inquiries and requests

  • Provide personalized solutions and recommendations

  • Follow up regularly to ensure satisfaction

  • Offer value-added services and resources

  • Maintain a positive and professional attitude

  • Be transparent and honest in all interactions

  • Show appreciation and gratitude for their business

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Q11. Formula for precision?

Ans.

Precision is the ratio of correctly predicted positive observations to the total predicted positive observations.

  • Precision = True Positives / (True Positives + False Positives)

  • It is a measure of the accuracy of the positive predictions made by the model.

  • A high precision indicates that the model is good at predicting positive cases without many false positives.

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Q12. Tell me what is endorsement Have you use system and online

Ans.

Endorsement is the act of giving approval or support to something or someone.

  • Endorsement can be in the form of a written or spoken statement of approval.

  • It can also be a signature on a document to show support or agreement.

  • Endorsement is commonly used in politics, advertising, and social media.

  • For example, a celebrity endorsing a product can increase its popularity and sales.

  • In online systems, endorsement can be in the form of likes, shares, or positive reviews.

  • Endorsement ca...read more

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Q13. What is lvm and what's working

Ans.

LVM (Logical Volume Manager) is a tool used to manage disk storage in Linux systems by creating logical volumes from physical volumes.

  • LVM allows for dynamic resizing of logical volumes without the need to unmount the filesystem.

  • It provides features like striping, mirroring, and snapshotting for better data management.

  • Commands like pvcreate, vgcreate, lvcreate are used to create physical volumes, volume groups, and logical volumes respectively.

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Q14. how to use vlookup

Ans.

VLOOKUP is a function in Excel used to search for a value in a table and return a corresponding value from another column.

  • VLOOKUP stands for vertical lookup.

  • It is commonly used to find data in large datasets or tables.

  • The function requires four arguments: lookup value, table array, column index number, and range lookup.

  • The lookup value is the value you want to search for.

  • The table array is the range of cells that contains the data.

  • The column index number is the column from wh...read more

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Q15. Slicing in List of Python

Ans.

Slicing in Python allows you to extract a subset of elements from a list.

  • Slicing is done using square brackets and the start:stop:step notation.

  • The start index is inclusive, while the stop index is exclusive.

  • You can omit any of the three parameters, defaulting to 0 for start, length of list for stop, and 1 for step.

  • Negative indices can be used to slice from the end of the list.

  • Example: list = [1, 2, 3, 4, 5], list[1:4] will return [2, 3, 4].

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Q16. Different yum and wget command

Ans.

yum is a package manager for Red Hat-based systems, while wget is a command-line tool for downloading files from the internet.

  • yum is used for installing, updating, and removing packages on Red Hat-based systems

  • wget is used for downloading files from the internet, supports HTTP, HTTPS, and FTP protocols

  • yum command example: yum install httpd

  • wget command example: wget https://example.com/file.zip

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