{"id":25588440,"date":"2024-07-17T11:36:45","date_gmt":"2024-07-17T06:06:45","guid":{"rendered":"https:\/\/entri.app\/blog\/?p=25588440"},"modified":"2025-07-25T19:00:53","modified_gmt":"2025-07-25T13:30:53","slug":"tech-mahindra-data-science-interview-questions","status":"publish","type":"post","link":"https:\/\/entri.app\/blog\/tech-mahindra-data-science-interview-questions\/","title":{"rendered":"26 Tech Mahindra Data Science Interview Questions"},"content":{"rendered":"<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_79_2 counter-hierarchy ez-toc-counter ez-toc-custom ez-toc-container-direction\">\n<p class=\"ez-toc-title\" style=\"cursor:inherit\">Table of Contents<\/p>\n<label for=\"ez-toc-cssicon-toggle-item-6a03e2c40ac77\" class=\"ez-toc-cssicon-toggle-label\"><span class=\"\"><span class=\"eztoc-hide\" style=\"display:none;\">Toggle<\/span><span class=\"ez-toc-icon-toggle-span\"><svg style=\"fill: #999;color:#999\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" class=\"list-377408\" width=\"20px\" height=\"20px\" viewBox=\"0 0 24 24\" fill=\"none\"><path d=\"M6 6H4v2h2V6zm14 0H8v2h12V6zM4 11h2v2H4v-2zm16 0H8v2h12v-2zM4 16h2v2H4v-2zm16 0H8v2h12v-2z\" fill=\"currentColor\"><\/path><\/svg><svg style=\"fill: #999;color:#999\" class=\"arrow-unsorted-368013\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"10px\" height=\"10px\" viewBox=\"0 0 24 24\" version=\"1.2\" baseProfile=\"tiny\"><path d=\"M18.2 9.3l-6.2-6.3-6.2 6.3c-.2.2-.3.4-.3.7s.1.5.3.7c.2.2.4.3.7.3h11c.3 0 .5-.1.7-.3.2-.2.3-.5.3-.7s-.1-.5-.3-.7zM5.8 14.7l6.2 6.3 6.2-6.3c.2-.2.3-.5.3-.7s-.1-.5-.3-.7c-.2-.2-.4-.3-.7-.3h-11c-.3 0-.5.1-.7.3-.2.2-.3.5-.3.7s.1.5.3.7z\"\/><\/svg><\/span><\/span><\/label><input type=\"checkbox\"  id=\"ez-toc-cssicon-toggle-item-6a03e2c40ac77\"  aria-label=\"Toggle\" \/><nav><ul class='ez-toc-list ez-toc-list-level-1 ' ><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-1\" href=\"https:\/\/entri.app\/blog\/tech-mahindra-data-science-interview-questions\/#Why_Join_Tech_Mahindra_as_a_Data_Scientist\" >Why Join Tech Mahindra as a Data Scientist?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/entri.app\/blog\/tech-mahindra-data-science-interview-questions\/#Tech_Mahindra_Data_Science_Interview_Preparation_Tips\" >Tech Mahindra Data Science Interview Preparation Tips:<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/entri.app\/blog\/tech-mahindra-data-science-interview-questions\/#Top_Tech_Mahindra_Data_Science_Interview_Questions_and_Answers\" >Top Tech Mahindra Data Science Interview Questions and Answers<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/entri.app\/blog\/tech-mahindra-data-science-interview-questions\/#Tech_Mahindra_Data_Science_Interview_Conclusion\" >Tech Mahindra Data Science Interview: Conclusion<\/a><\/li><\/ul><\/nav><\/div>\n<p>Tech Mahindra is a Multinational company, having its presence in over 90 countries around the globe. It is known for its customer-centric approach. Tech Mahindra&#8217;s key areas include AI, IoT, Blockchain and Data Science technology. Getting a job in this prestigious company is a dream come true for many candidates who wish to build a career in the digital field. In this article we will be covering some Tech Mahindra Data Science Interview Questions.<\/p>\n<div class=\"flex flex-grow flex-col max-w-full\">\n<div class=\"min-h-[20px] text-message flex flex-col items-start whitespace-pre-wrap break-words [.text-message+&amp;]:mt-5 juice:w-full juice:items-end overflow-x-auto gap-2\" dir=\"auto\" data-message-author-role=\"assistant\" data-message-id=\"01941ee9-a7ec-445e-9cb9-3e0e1ac6a038\">\n<div class=\"flex w-full flex-col gap-1 juice:empty:hidden juice:first:pt-[3px]\">\n<div class=\"markdown prose w-full break-words dark:prose-invert light\">\n<p style=\"text-align: center;\"><strong><a href=\"https:\/\/entri.app\/course\/data-science-and-machine-learning-course\/\" target=\"_blank\" rel=\"noopener\">Enhance your data science skills with us! Join our free demo today!<\/a><\/strong><\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<h2><span class=\"ez-toc-section\" id=\"Why_Join_Tech_Mahindra_as_a_Data_Scientist\"><\/span><span data-sheets-root=\"1\" data-sheets-value=\"{&quot;1&quot;:2,&quot;2&quot;:&quot;Introduction\\nWhy Join Tech Mahindra as a Data Scientist\\nTech Mahindra Data Science Interview Preparation Tips\\nTop Tech Mahindra Data Science Interview Questions and answers&quot;}\" data-sheets-userformat=\"{&quot;2&quot;:769,&quot;3&quot;:{&quot;1&quot;:0},&quot;11&quot;:4,&quot;12&quot;:0}\"><strong>Why Join Tech Mahindra as a Data Scientist?<\/strong><\/span><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Tech Mahindra provides an exciting environment for data scientists to work on diverse, cutting-edge projects, grow their careers, and make a global impact.<\/p>\n<ul>\n<li><strong>Exciting Projects:<\/strong>\n<ul>\n<li>Work on innovative digital projects in diverse industries like telecommunications and healthcare.<\/li>\n<li>Apply advanced analytics and machine learning to tackle real-world challenges.<\/li>\n<\/ul>\n<\/li>\n<li><strong>Career Growth:<\/strong>\n<ul>\n<li>Access opportunities for continuous learning and professional development.<\/li>\n<li>Collaborate with global teams in a supportive and dynamic environment.<\/li>\n<\/ul>\n<\/li>\n<li><strong>Cutting-Edge Technology:<\/strong>\n<ul>\n<li>Utilize AI, IoT, and blockchain technologies to drive impactful solutions.<\/li>\n<li>Stay at the forefront of technology trends and innovations in data science.<\/li>\n<\/ul>\n<\/li>\n<li><strong>Global Impact:<\/strong>\n<ul>\n<li>Contribute to solutions that shape the future of global industries.<\/li>\n<li>Make a meaningful impact through data-driven insights and strategies.<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<div class=\"lead-gen-block\"><a href=\"https:\/\/entri.app\/blog\/wp-content\/uploads\/2024\/07\/Tech-Mahindra-Data-Science-Interview-Questions.pdf\" data-url=\"https:\/\/entri.app\/blog\/wp-content\/uploads\/2024\/07\/Tech-Mahindra-Data-Science-Interview-Questions.pdf\" class=\"lead-pdf-download\" data-id=\"25556851\">\n<p style=\"text-align: center;\"><button class=\"btn btn-default\">download tech mahindra data science interview questions Now!<\/button><\/p>\n<\/a><\/div>\n<h2><span class=\"ez-toc-section\" id=\"Tech_Mahindra_Data_Science_Interview_Preparation_Tips\"><\/span><span data-sheets-root=\"1\" data-sheets-value=\"{&quot;1&quot;:2,&quot;2&quot;:&quot;Introduction\\nWhy Join Tech Mahindra as a Data Scientist\\nTech Mahindra Data Science Interview Preparation Tips\\nTop Tech Mahindra Data Science Interview Questions and answers&quot;}\" data-sheets-userformat=\"{&quot;2&quot;:769,&quot;3&quot;:{&quot;1&quot;:0},&quot;11&quot;:4,&quot;12&quot;:0}\"><strong>Tech Mahindra Data Science Interview Preparation Tips:<\/strong><br \/>\n<\/span><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p><strong>1. Understand Tech Mahindra&#8217;s Focus:<\/strong><\/p>\n<ul>\n<li>Research recent projects and industries served by Tech Mahindra.<\/li>\n<li>Align your skills with their technological initiatives.<\/li>\n<\/ul>\n<p><strong>2. Review Data Science Fundamentals:<\/strong><\/p>\n<ul>\n<li>Refresh knowledge of machine learning algorithms and statistical analysis.<\/li>\n<li>Practice data manipulation using Python or R.<\/li>\n<\/ul>\n<p><strong>3. Practice Coding:<\/strong><\/p>\n<ul>\n<li>Master Python or R programming for data analysis.<\/li>\n<li>Practice solving data science problems using libraries like NumPy and Pandas.<\/li>\n<\/ul>\n<p><strong>4. Know Your Algorithms:<\/strong><\/p>\n<ul>\n<li>Understand key algorithms like linear regression and decision trees.<\/li>\n<li>Be prepared to discuss their applications in data science.<\/li>\n<\/ul>\n<p><strong>5. Prepare for Case Studies:<\/strong><\/p>\n<ul>\n<li>Have examples ready from past projects or scenarios.<\/li>\n<li>Demonstrate problem-solving skills and data analysis approaches.<\/li>\n<\/ul>\n<p><strong>6. Be Familiar with Big Data Technologies:<\/strong><\/p>\n<ul>\n<li>Learn about tools like Hadoop and Spark for big data processing.<\/li>\n<li>Understand cloud platforms such as AWS or Azure for data science applications.<\/li>\n<\/ul>\n<p><strong>7. Communicate Clearly:<\/strong><\/p>\n<ul>\n<li>Practice explaining technical concepts concisely.<\/li>\n<li>Be ready to articulate how your skills meet Tech Mahindra&#8217;s needs.<\/li>\n<\/ul>\n<p><strong>8. Stay Updated:<\/strong><\/p>\n<ul>\n<li>Keep informed about the latest trends in data science and technology.<\/li>\n<li>Follow industry news and advancements in machine learning and AI.<\/li>\n<\/ul>\n<h2><span class=\"ez-toc-section\" id=\"Top_Tech_Mahindra_Data_Science_Interview_Questions_and_Answers\"><\/span><strong>Top Tech Mahindra Data Science Interview Questions and Answers<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p><strong>1. How to deploy a model on the cloud?<\/strong><\/p>\n<p><strong>Ans.<\/strong> Deploying a model on the cloud typically involves:<\/p>\n<ul>\n<li style=\"list-style-type: none;\">\n<ul>\n<li>Selecting a cloud provider (e.g., AWS, Azure, GCP).<\/li>\n<li>Packaging the model with its dependencies.<\/li>\n<li>Creating a Docker container if needed.<\/li>\n<li>Using cloud services (e.g., AWS SageMaker, Azure ML) to deploy and manage the model.<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<p><strong>2. Azure vs. AWS:<\/strong><\/p>\n<p><strong>Ans.<\/strong><\/p>\n<ul>\n<li style=\"list-style-type: none;\">\n<ul>\n<li><strong>Azure<\/strong>: Strong integration with Microsoft products, better for enterprises already using Microsoft services, offers a wide range of AI and machine learning tools.<\/li>\n<li><strong>AWS<\/strong>: Market leader with a vast array of services, strong ecosystem for machine learning (e.g., SageMaker), extensive global infrastructure.<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<p><strong>3. Dockerfile vs. Docker Compose YAML:<\/strong><\/p>\n<p><strong>Ans.<\/strong><\/p>\n<ul>\n<li style=\"list-style-type: none;\">\n<ul>\n<li><strong>Dockerfile<\/strong>: A script containing a series of instructions on how to build a Docker image.<\/li>\n<li><strong>Docker Compose YAML<\/strong>: A configuration file for defining and running multi-container Docker applications, managing multiple Docker containers.<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<p><strong>4. Pipeline from code development to model deployment:<\/strong><\/p>\n<p><strong>Ans.<\/strong><\/p>\n<ul>\n<li style=\"list-style-type: none;\">\n<ul>\n<li><strong>Code Development<\/strong>: Write and test your code locally.<\/li>\n<li><strong>Version Control<\/strong>: Use Git to manage code versions.<\/li>\n<li><strong>Continuous Integration<\/strong>: Use CI tools (e.g., Jenkins) to run tests.<\/li>\n<li><strong>Containerization<\/strong>: Package the application using Docker.<\/li>\n<li><strong>Deployment<\/strong>: Deploy the container to the cloud using services like Kubernetes or cloud-specific offerings.<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<p><strong>5. What is Jenkins pipeline?\u00a0<\/strong><\/p>\n<p><strong>Ans. Jenkins Pipeline<\/strong>: An automated process for building, testing, and deploying code, defined as code using the Groovy-based DSL.<\/p>\n<p><strong>6. How do you use Jenkins to automate CI\/CD?<\/strong><\/p>\n<p><strong>Ans.<\/strong> By setting up Jenkins pipelines to automate the build, test, and deployment processes, integrating with version control, and configuring various stages of the pipeline.<\/p>\n<p><strong>7. When will a model be redeployed?<\/strong><\/p>\n<p><strong>Ans.<\/strong> A model will be redeployed when:<\/p>\n<ul>\n<li style=\"list-style-type: none;\">\n<ul>\n<li>The model is retrained with new data.<\/li>\n<li>Improvements or updates are made to the model.<\/li>\n<li>There are changes in the production environment or dependencies.<\/li>\n<li>Performance issues or bugs are detected in the current deployment.<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<p><strong>8. How does AWS handle multiple models deployed in production simultaneously?<\/strong><\/p>\n<p><strong>Ans.<\/strong> AWS handles multiple models in production using services like:<\/p>\n<ul>\n<li style=\"list-style-type: none;\">\n<ul>\n<li><strong>AWS SageMaker Endpoints<\/strong>: Create multiple endpoints for different models.<\/li>\n<li><strong>Load Balancing<\/strong>: Use Elastic Load Balancing to distribute traffic among multiple models.<\/li>\n<li><strong>Container Orchestration<\/strong>: Use ECS or EKS to manage multiple model containers efficiently.<\/li>\n<li><strong>Monitoring and Scaling<\/strong>: Use CloudWatch for monitoring and auto-scaling groups for automatic scaling based on demand.<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<p style=\"text-align: center;\"><span data-sheets-root=\"1\" data-sheets-value=\"{&quot;1&quot;:2,&quot;2&quot;:&quot; Introduction\\r\\nUnderstanding Data Visualization using Power BI \\r\\n Importance of Implementing Best Practices in Power BI Data Visualization\\r\\nPower bi data visualization Best practice ( list down the best practices )\\r\\nTechniques for Power BI Data Visualization\\r\\nconclusion\\r&quot;}\" data-sheets-userformat=\"{&quot;2&quot;:769,&quot;3&quot;:{&quot;1&quot;:0},&quot;11&quot;:4,&quot;12&quot;:0}\"><strong><a class=\"in-cell-link\" href=\"https:\/\/entri.app\/course\/data-science-and-machine-learning-course\/\" target=\"_blank\" rel=\"noopener\">Ready to take your data science skills to the next level? Sign up for a free demo today!<\/a><\/strong><\/span><\/p>\n<h5><strong>SQL Basic Queries<\/strong><\/h5>\n<p><strong>9. How do you write a query to select all columns from a table named employees?<\/strong><\/p>\n<p><strong>Ans.<\/strong> SELECT * FROM employees;<\/p>\n<p><strong>10. How do you filter records in the employees table where the salary is greater than 50000?<\/strong><\/p>\n<p><strong>Ans.<\/strong> SELECT * FROM employees WHERE salary &gt; 50000;<\/p>\n<p><strong>11. How do you find the average salary of employees grouped by department?<\/strong><\/p>\n<p><strong>Ans. SQL Code<\/strong><\/p>\n<div class=\"dark bg-gray-950 rounded-md border-[0.5px] border-token-border-medium\">\n<div class=\"overflow-y-auto p-4\" dir=\"ltr\">SELECT department, AVG(salary) AS average_salary<br \/>\nFROM employees<br \/>\nGROUP BY department;<\/div>\n<\/div>\n<p><strong>12.\u00a0 How do you join two tables, employees and departments, on the department_id column?<\/strong><\/p>\n<p><strong>Ans. SQL code<\/strong><\/p>\n<p>SELECT e.*, d.department_name<br \/>\nFROM employees e<br \/>\nJOIN departments d ON e.department_id = d.department_id;<\/p>\n<h5><strong>Unnecessary Definition from SQL<\/strong><\/h5>\n<p><strong>13. What is an unnecessary definition in SQL?<\/strong><\/p>\n<p><strong>Ans.<\/strong> An unnecessary definition in SQL refers to defining redundant or non-essential elements in a query, such as selecting columns that are not used, using subqueries when a JOIN is sufficient, or including complex expressions that do not enhance the query&#8217;s functionality or performance.<\/p>\n<h5><strong>Linear and Logistic Regression<\/strong><\/h5>\n<p><strong>14. What is Linear Regression?<\/strong><\/p>\n<p><strong>Ans.\u00a0<\/strong> Linear Regression is a supervised learning algorithm used for predicting a continuous dependent variable based on one or more independent variables by fitting a linear relationship between them.<\/p>\n<p><strong>15. What is Logistic Regression?<\/strong><\/p>\n<p><strong>Ans.\u00a0<\/strong> Logistic Regression is a supervised learning algorithm used for binary classification tasks. It predicts the probability of a binary outcome using a logistic function to model the relationship between the dependent variable and one or more independent variables.<\/p>\n<h5><strong>Decision Tree and Random Forest<\/strong><\/h5>\n<p><strong>16. What is a Decision Tree?<\/strong><\/p>\n<p><strong>Ans.<\/strong>\u00a0 A Decision Tree is a supervised learning algorithm used for both classification and regression tasks. It splits the data into subsets based on the value of input features, creating a tree-like model of decisions.<\/p>\n<p><strong>17. What is a Random Forest?<\/strong><\/p>\n<p><strong>Ans.<\/strong> A Random Forest is an ensemble learning method that combines multiple decision trees to improve the model&#8217;s accuracy and prevent overfitting. It creates a &#8216;forest&#8217; of random decision trees and aggregates their predictions.<\/p>\n<h5><strong>Naive Bayes Theory<\/strong><\/h5>\n<p><strong>18. What is Naive Bayes Theory?<\/strong><\/p>\n<p><strong>Ans.\u00a0<\/strong> Naive Bayes is a probabilistic classification algorithm based on Bayes&#8217; Theorem. It assumes independence between the features and calculates the probability of each class based on the input features, selecting the class with the highest probability.<\/p>\n<h5><strong>How to Handle Null Values in a Dataset<\/strong><\/h5>\n<p><strong>19. How do you handle null values in a dataset?<\/strong><\/p>\n<p><strong>Ans.<\/strong>\u00a0 Handling null values can be done in several ways:<\/p>\n<ul>\n<li><strong>Removal<\/strong>: Remove rows or columns with null values.<\/li>\n<li><strong>Imputation<\/strong>: Fill null values with a specific value like the mean, median, mode, or a fixed value.<\/li>\n<li><strong>Prediction<\/strong>: Use predictive models to estimate and replace null values.<\/li>\n<li><strong>Flagging<\/strong>: Create a separate binary feature indicating the presence of null values.<\/li>\n<\/ul>\n<p><strong>20. What are your favorite libraries in Python?<\/strong><\/p>\n<p><strong>Ans.<\/strong> One of my favorite libraries in Python is <strong>Pandas<\/strong>. It&#8217;s great for data manipulation and analysis. With Pandas, you can easily read data from different file formats, clean it, and perform various operations to get insights quickly. Another favorite is <strong>NumPy<\/strong>, which is essential for numerical computations and handling arrays efficiently. Lastly, I really like <strong>Matplotlib<\/strong> for creating visualizations; it makes it easy to generate plots and charts to understand data better. For example, I often use Pandas to clean my datasets, NumPy to perform calculations, and Matplotlib to visualize the results.<\/p>\n<p><strong>22. What is the difference between Logistic and Linear Regression?<\/strong><\/p>\n<p><strong>Ans.<\/strong><\/p>\n<p><strong>Linear Regression:<\/strong><\/p>\n<ul>\n<li><strong>Purpose<\/strong>: Predicts a continuous outcome based on input variables.<\/li>\n<li><strong>Output<\/strong>: Gives a straight-line prediction (like predicting house prices).<\/li>\n<li><strong>Equation<\/strong>: Uses a simple linear equation to find a relationship between variables.<\/li>\n<li><strong>Use<\/strong>: Best for tasks where the result is a number.<\/li>\n<\/ul>\n<p><strong>Logistic Regression:<\/strong><\/p>\n<ul>\n<li><strong>Purpose<\/strong>: Predicts the probability of a categorical outcome.<\/li>\n<li><strong>Output<\/strong>: Provides probabilities that map to binary outcomes (like yes\/no or spam\/not spam).<\/li>\n<li><strong>Equation<\/strong>: Uses a logistic function to model the probability.<\/li>\n<li><strong>Use<\/strong>: Ideal for tasks where the result is a category.<\/li>\n<\/ul>\n<p><strong>Key Differences:<\/strong><\/p>\n<ul>\n<li><strong>Output Type<\/strong>: Linear regression predicts numbers; logistic regression predicts probabilities.<\/li>\n<li><strong>Application<\/strong>: Linear regression for numbers, logistic regression for categories.<\/li>\n<\/ul>\n<p>In essence, linear regression predicts numbers (like house prices), while logistic regression predicts probabilities and maps them to categories (like yes\/no).<\/p>\n<div class=\"flex flex-grow flex-col max-w-full\">\n<div class=\"min-h-[20px] text-message flex flex-col items-start whitespace-pre-wrap break-words [.text-message+&amp;]:mt-5 juice:w-full juice:items-end overflow-x-auto gap-2\" dir=\"auto\" data-message-author-role=\"assistant\" data-message-id=\"ca020c14-ae9e-473d-868a-8ee09ae6d265\">\n<div class=\"flex w-full flex-col gap-1 juice:empty:hidden juice:first:pt-[3px]\">\n<div class=\"markdown prose w-full break-words dark:prose-invert light\">\n<p><strong>23. What is the difference between data science and big data?<\/strong><\/p>\n<p><strong>Ans.<\/strong><\/p>\n<p><strong>Data Science:<\/strong><\/p>\n<ul>\n<li><strong>Focus<\/strong>: Using data to solve problems and make decisions.<\/li>\n<li><strong>Tasks<\/strong>: Analyzing, visualizing, and modeling data to find insights.<\/li>\n<li><strong>Tools<\/strong>: Statistics, machine learning, Python\/R programming.<\/li>\n<\/ul>\n<p><strong>Big Data:<\/strong><\/p>\n<ul>\n<li><strong>Focus<\/strong>: Dealing with large and complex datasets.<\/li>\n<li><strong>Characteristics<\/strong>: High volume, speed, and variety of data.<\/li>\n<li><strong>Challenges<\/strong>: Storing, managing, and analyzing massive amounts of data efficiently.<\/li>\n<\/ul>\n<p><strong>Key Differences:<\/strong><\/p>\n<ul>\n<li><strong>Focus<\/strong>: Data science analyzes data; big data handles large datasets.<\/li>\n<li><strong>Tools<\/strong>: Data science uses stats and ML; big data uses special tech for storage and processing.<\/li>\n<\/ul>\n<p>In essence, data science applies tools to analyze data for insights, while big data deals with storing and managing large, varied datasets efficiently.<\/p>\n<p><strong>24. What is Word2Vec?<\/strong><\/p>\n<p><strong>Ans. <\/strong>\u00a0Word2Vec is a technique in natural language processing (NLP) used to convert words into vectors of numerical values. It captures semantic relationships between words based on their contexts in large datasets.<\/p>\n<p><strong>25. What is TF-IDF?<\/strong><\/p>\n<p><strong>Ans.<\/strong> TF-IDF (Term Frequency-Inverse Document Frequency) is a statistical measure used to evaluate the importance of a word in a document relative to a collection of documents. It reflects how frequently a term appears in a document adjusted by how often it appears across all documents.<\/p>\n<p><strong>26. How do you use regex to remove special characters from a text?<\/strong><\/p>\n<p><strong>Ans. Python code:<\/strong><\/p>\n<p>import re<\/p>\n<p>text = &#8220;Hello! This is a sample text with @special characters #included.&#8221;<br \/>\nclean_text = re.sub(r'[^a-zA-Z0-9\\s]&#8217;, &#8221;, text)<br \/>\nprint(clean_text)<\/p>\n<p><strong>Explanation:<\/strong><\/p>\n<ul>\n<li>r'[^a-zA-Z0-9\\s]&#8217;: This regex pattern matches any character that is not alphanumeric (a-z, A-Z, 0-9) or whitespace (\\s).<\/li>\n<li>re.sub(r'[^a-zA-Z0-9\\s]&#8217;, &#8221;, text): This function call replaces all characters matching the pattern with an empty string, effectively removing them from the text.<\/li>\n<\/ul>\n<p style=\"text-align: center;\"><span data-sheets-root=\"1\" data-sheets-value=\"{&quot;1&quot;:2,&quot;2&quot;:&quot; Introduction\\r\\nUnderstanding Data Visualization using Power BI \\r\\n Importance of Implementing Best Practices in Power BI Data Visualization\\r\\nPower bi data visualization Best practice ( list down the best practices )\\r\\nTechniques for Power BI Data Visualization\\r\\nconclusion\\r&quot;}\" data-sheets-userformat=\"{&quot;2&quot;:769,&quot;3&quot;:{&quot;1&quot;:0},&quot;11&quot;:4,&quot;12&quot;:0}\"><strong><a class=\"in-cell-link\" href=\"https:\/\/entri.app\/course\/data-science-and-machine-learning-course\/\" target=\"_blank\" rel=\"noopener\">Ready to take your data science skills to the next level? Sign up for a free demo today!<\/a><\/strong><\/span><\/p>\n<h2><span class=\"ez-toc-section\" id=\"Tech_Mahindra_Data_Science_Interview_Conclusion\"><\/span><strong>Tech Mahindra Data Science Interview: Conclusion<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>We have provided you with some interview questions for data science jobs at Tech Mahindra.\u00a0 The candidates can use them as a sample to prepare for their data science interviews at Tech Mahindra. These are a combination of the most common questions as well as the top questions asked at the interviews. These questions can be reviewed and studied to have a better and fruitful interview.<\/p>\n<p>If you feel like understanding and learning data science thoroughly, consider enrolling in Entri&#8217;s Data Science course. With industry experts as mentors and top-notch materials for practical understanding, this course is your best way to crack the interview. So, enrol now and secure your future with Entri. All the best!<\/p>\n<table>\n<tbody>\n<tr>\n<td colspan=\"2\">\n<p style=\"text-align: center;\"><b>Related Articles<\/b><\/p>\n<\/td>\n<\/tr>\n<tr>\n<td><a href=\"https:\/\/entri.app\/blog\/data-science-interview-questions-answers\/\" target=\"_blank\" rel=\"noopener\"><b>Top 100 Data Science Interview Questions<\/b><\/a><\/td>\n<td><a href=\"https:\/\/entri.app\/blog\/google-data-science-interview-questions\/\" target=\"_blank\" rel=\"noopener\"><b>Google Data Science Interview Questions<\/b><\/a><\/td>\n<\/tr>\n<tr>\n<td><a href=\"https:\/\/entri.app\/blog\/deloitte-data-scientist-interview-questions\/\" target=\"_blank\" rel=\"noopener\"><b>Deloitte Data Scientist Interview Questions<\/b><\/a><\/td>\n<td><a href=\"https:\/\/entri.app\/blog\/amazon-data-science-interview-questions\/\" target=\"_blank\" rel=\"noopener\"><b>Amazon Data Science Interview Questions<\/b><\/a><\/td>\n<\/tr>\n<tr>\n<td><a href=\"https:\/\/entri.app\/blog\/genpact-data-science-interview-questions\/\" target=\"_blank\" rel=\"noopener\"><b>Genpact Data Science Interview Questions<\/b><\/a><\/td>\n<td><a href=\"https:\/\/entri.app\/blog\/accenture-data-science-interview-questions\/\" target=\"_blank\" rel=\"noopener\"><b>Accenture Data Science Interview Questions<\/b><\/a><\/td>\n<\/tr>\n<tr>\n<td><a href=\"https:\/\/entri.app\/blog\/capgemini-data-science-interview-questions\/\" target=\"_blank\" rel=\"noopener\"><b>Capgemini Data Science Interview Questions<\/b><\/a><\/td>\n<td><a href=\"https:\/\/entri.app\/blog\/data-science-interview-tips\/\" target=\"_blank\" rel=\"noopener\"><b>Mastering the Art of Data Science Interview &#8211; Tips and Tricks<\/b><\/a><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<div class=\"modal\" id=\"modal25556851\"><div class=\"modal-content\"><span class=\"close-button\">&times;<\/span>\n\n<div class=\"wpcf7 no-js\" id=\"wpcf7-f25556851-o1\" lang=\"en-US\" dir=\"ltr\" data-wpcf7-id=\"25556851\">\n<div class=\"screen-reader-response\"><p role=\"status\" aria-live=\"polite\" aria-atomic=\"true\"><\/p> <ul><\/ul><\/div>\n<form action=\"\/blog\/wp-json\/wp\/v2\/posts\/25588440#wpcf7-f25556851-o1\" method=\"post\" class=\"wpcf7-form init\" aria-label=\"Contact form\" novalidate=\"novalidate\" data-status=\"init\">\n<fieldset class=\"hidden-fields-container\"><input type=\"hidden\" name=\"_wpcf7\" value=\"25556851\" \/><input type=\"hidden\" name=\"_wpcf7_version\" value=\"6.1.4\" \/><input type=\"hidden\" name=\"_wpcf7_locale\" value=\"en_US\" \/><input type=\"hidden\" name=\"_wpcf7_unit_tag\" value=\"wpcf7-f25556851-o1\" \/><input type=\"hidden\" name=\"_wpcf7_container_post\" value=\"0\" \/><input type=\"hidden\" name=\"_wpcf7_posted_data_hash\" value=\"\" \/><input type=\"hidden\" name=\"_wpcf7cf_hidden_group_fields\" value=\"[]\" \/><input type=\"hidden\" name=\"_wpcf7cf_hidden_groups\" value=\"[]\" \/><input type=\"hidden\" name=\"_wpcf7cf_visible_groups\" value=\"[]\" \/><input type=\"hidden\" name=\"_wpcf7cf_repeaters\" value=\"[]\" \/><input type=\"hidden\" name=\"_wpcf7cf_steps\" value=\"{}\" \/><input type=\"hidden\" name=\"_wpcf7cf_options\" value=\"{&quot;form_id&quot;:25556851,&quot;conditions&quot;:[],&quot;settings&quot;:{&quot;animation&quot;:&quot;yes&quot;,&quot;animation_intime&quot;:200,&quot;animation_outtime&quot;:200,&quot;conditions_ui&quot;:&quot;normal&quot;,&quot;notice_dismissed&quot;:false,&quot;notice_dismissed_update-cf7-5.9.8&quot;:true,&quot;notice_dismissed_update-cf7-6.1.1&quot;:true}}\" \/>\n<\/fieldset>\n<p><span class=\"wpcf7-form-control-wrap\" data-name=\"full_name\"><input size=\"40\" maxlength=\"400\" class=\"wpcf7-form-control wpcf7-text wpcf7-validates-as-required\" aria-required=\"true\" aria-invalid=\"false\" placeholder=\"Name\" value=\"\" type=\"text\" name=\"full_name\" \/><\/span><br \/>\n<span class=\"wpcf7-form-control-wrap\" data-name=\"phone\"><input size=\"40\" maxlength=\"400\" class=\"wpcf7-form-control wpcf7-tel wpcf7-validates-as-required wpcf7-text wpcf7-validates-as-tel\" aria-required=\"true\" aria-invalid=\"false\" placeholder=\"Phone\" value=\"\" type=\"tel\" name=\"phone\" \/><\/span><br \/>\n<span class=\"wpcf7-form-control-wrap\" data-name=\"email_id\"><input size=\"40\" maxlength=\"400\" class=\"wpcf7-form-control wpcf7-email wpcf7-text wpcf7-validates-as-email\" aria-invalid=\"false\" placeholder=\"Email\" value=\"\" type=\"email\" name=\"email_id\" \/><\/span>\n<\/p>\n<div class=\"custom-form-group-1\">\n\t<p><span class=\"wpcf7-form-control-wrap\" data-name=\"language\"><select class=\"wpcf7-form-control wpcf7-select wpcf7-validates-as-required language-select1\" aria-required=\"true\" aria-invalid=\"false\" name=\"language\"><option value=\"\">Select Language<\/option><option value=\"Malayalam\">Malayalam<\/option><option value=\"Tamil\">Tamil<\/option><option value=\"Telugu\">Telugu<\/option><option value=\"Kannada\">Kannada<\/option><\/select><\/span>\n\t<\/p>\n<\/div>\n<div class=\"custom-form-group-1\">\n\t<p><span class=\"wpcf7-form-control-wrap\" data-name=\"course\"><select class=\"wpcf7-form-control wpcf7-select wpcf7-validates-as-required course-select1\" aria-required=\"true\" aria-invalid=\"false\" name=\"course\"><option value=\"\">Select an option<\/option><option value=\"Kerala PSC Exams\">Kerala PSC Exams<\/option><option value=\"Kerala PSC Teaching Exams\">Kerala PSC Teaching Exams<\/option><option value=\"Kerala PSC Technical Exams\">Kerala PSC Technical Exams<\/option><option value=\"SSC\/RRB\">SSC\/RRB<\/option><option value=\"GATE\">GATE<\/option><option value=\"Banking &amp; Insurance\">Banking &amp; Insurance<\/option><option value=\"Coding\">Coding<\/option><option value=\"Commerce\">Commerce<\/option><option value=\"Personal Finance\">Personal Finance<\/option><option value=\"Spoken English\/Personality Dev\">Spoken English\/Personality Dev<\/option><option value=\"German Language\">German Language<\/option><option value=\"Montessori Teacher Training\">Montessori Teacher Training<\/option><option value=\"IELTS\">IELTS<\/option><option value=\"MEP\">MEP<\/option><option value=\"Quantity Surveying\">Quantity Surveying<\/option><option value=\"Structural Design\">Structural Design<\/option><option value=\"Yoga TTC\">Yoga TTC<\/option><option value=\"Digital Marketing\">Digital Marketing<\/option><option value=\"Hospital and Healthcare Administration\">Hospital and Healthcare Administration<\/option><option value=\"BIM\">BIM<\/option><option value=\"HR Management\">HR Management<\/option><option value=\"Embedded System Software Engineering\">Embedded System Software Engineering<\/option><\/select><\/span>\n\t<\/p>\n<\/div>\n<div class=\"custom-form-group-1\">\n\t<p><span class=\"wpcf7-form-control-wrap\" data-name=\"course_name\"><select class=\"wpcf7-form-control wpcf7-select wpcf7-validates-as-required course-name-select1\" aria-required=\"true\" aria-invalid=\"false\" name=\"course_name\"><option value=\"\">Select an option<\/option><option value=\"KAS\">KAS<\/option><option value=\"Degree level\">Degree level<\/option><option value=\"12th level\">12th level<\/option><option value=\"10th level\">10th level<\/option><option value=\"Secretariat Assistant\">Secretariat Assistant<\/option><option value=\"LDC\">LDC<\/option><option value=\"LGS\">LGS<\/option><option value=\"University Assistant\">University Assistant<\/option><option value=\"FSO\">FSO<\/option><option value=\"VEO\">VEO<\/option><option value=\"VFA\">VFA<\/option><option value=\"Dental Surgeon\">Dental Surgeon<\/option><option value=\"Staff Nurse\">Staff Nurse<\/option><option value=\"Sub Inspector\">Sub Inspector<\/option><option value=\"Divisional Accountant\">Divisional Accountant<\/option><option value=\"Fireman\/Firewomen\/Driver\">Fireman\/Firewomen\/Driver<\/option><option value=\"CPO\/WCPO\/Driver\">CPO\/WCPO\/Driver<\/option><option value=\"Excise\">Excise<\/option><option value=\"LD Typist\">LD Typist<\/option><option value=\"Junior Health Inspector\">Junior Health Inspector<\/option><option value=\"Assistant Jailor\">Assistant Jailor<\/option><option value=\"Kerala High Court Assistant\">Kerala High Court Assistant<\/option><option value=\"Beat Forest Officer\">Beat Forest Officer<\/option><option value=\"Junior Employment Officer\">Junior Employment Officer<\/option><option value=\"Junior Lab Assistant\">Junior Lab Assistant<\/option><option value=\"Dewaswom Board LDC\">Dewaswom Board LDC<\/option><option value=\"LSGS\">LSGS<\/option><option value=\"SBCID\">SBCID<\/option><option value=\"IRB Regular wing\">IRB Regular wing<\/option><option value=\"Assistant Salesman\">Assistant Salesman<\/option><option value=\"Secretariat OA\">Secretariat OA<\/option><option value=\"Driver Cum OA\">Driver Cum OA<\/option><option value=\"Departmental Test\">Departmental Test<\/option><option value=\"HSST\">HSST<\/option><option value=\"HSA\">HSA<\/option><option value=\"SET\">SET<\/option><option value=\"KTET\">KTET<\/option><option value=\"LP UP\">LP UP<\/option><option value=\"KVS\">KVS<\/option><option value=\"Finger Print Searcher\">Finger Print Searcher<\/option><option value=\"Nursery School Teacher\">Nursery School Teacher<\/option><option value=\"Railway Teacher\">Railway Teacher<\/option><option value=\"Scientific Officer\">Scientific Officer<\/option><option value=\"Probation Officer\">Probation Officer<\/option><option value=\"ICDS\">ICDS<\/option><option value=\"Welfare Officer Gr. 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margin-bottom: -15px;\"> <div id=\"cf-turnstile-cf7-1696432705\" class=\"cf-turnstile\" data-sitekey=\"0x4AAAAAABVigxtkiZeGTu5L\" data-theme=\"light\" data-language=\"auto\" data-size=\"normal\" data-retry=\"auto\" data-retry-interval=\"1000\" data-action=\"contact-form-7\" data-appearance=\"always\"><\/div> <script>document.addEventListener(\"DOMContentLoaded\", function() { setTimeout(function(){ var e=document.getElementById(\"cf-turnstile-cf7-1696432705\"); e&&!e.innerHTML.trim()&&(turnstile.remove(\"#cf-turnstile-cf7-1696432705\"), turnstile.render(\"#cf-turnstile-cf7-1696432705\", {sitekey:\"0x4AAAAAABVigxtkiZeGTu5L\"})); }, 0); });<\/script> <br class=\"cf-turnstile-br cf-turnstile-br-cf7-1696432705\"> <style>#cf-turnstile-cf7-1696432705 { margin-left: -15px; }<\/style> <script>document.addEventListener(\"DOMContentLoaded\",function(){document.querySelectorAll('.wpcf7-form').forEach(function(e){e.addEventListener('submit',function(){if(document.getElementById('cf-turnstile-cf7-1696432705')){setTimeout(function(){turnstile.reset('#cf-turnstile-cf7-1696432705');},1000)}})})});<\/script> <\/div><br\/><input class=\"wpcf7-form-control wpcf7-submit has-spinner\" type=\"submit\" value=\"Submit\" \/>\n<\/p><div class=\"wpcf7-response-output\" aria-hidden=\"true\"><\/div>\n<\/form>\n<\/div>\n\n<\/div><\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":"<p>Tech Mahindra is a Multinational company, having its presence in over 90 countries around the globe. It is known for its customer-centric approach. Tech Mahindra&#8217;s key areas include AI, IoT, Blockchain and Data Science technology. Getting a job in this prestigious company is a dream come true for many candidates who wish to build a [&hellip;]<\/p>\n","protected":false},"author":42,"featured_media":25588443,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[802,1864,1841],"tags":[],"class_list":["post-25588440","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-articles","category-data-science-ml","category-entri-skilling"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.6 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>26 Tech Mahindra Data Science Interview Questions - Entri Blog<\/title>\n<meta name=\"description\" content=\"In this article we will be covering some Tech Mahindra Data Science Interview Questions for you to shine and secure your future.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/entri.app\/blog\/tech-mahindra-data-science-interview-questions\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"26 Tech Mahindra Data Science Interview Questions - 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