Quantum Data Engines India Data Scientist Interview Questions and Answers for Freshers

Q1. Project related questions from your CV
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Q1. Question on transformers
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Q2. Comparison of transfer learning and fintuning.
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Transfer learning involves using pre-trained models on a different task, while fine-tuning involves further training a pre-trained model on a specific task.
• Transfer learning uses knowledge gained from one task to improve learning on a different task.

• Fine-tuning involves adjusting the parameters of a pre-trained model to better fit a specific task.

• Transfer learning is faster and requires less data compared to training a...read more
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Q1. Basics of Data Science was asked
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Q1. About projects and technical side of project tech stack
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The first technical round will cover how computer vision works, including the advantages and disadvantages of regression and random forest. It will also include discussions on when to use precision and recall, methods to reduce false positives, and criteria for selecting different models. Additionally, disadvantages of PCA will be addressed, along with project-related questions. The second round will focus on standard aptitude tests, while the third round will involve a casual conversation with the Executive Vice President.

Normal aptitude questions

Q1. What is L1 and L2 Regularization?
Ans. 
L1 and L2 regularization are techniques used in machine learning to prevent overfitting by adding penalty terms to the cost function.
• L1 regularization adds the absolute values of the coefficients as penalty term to the cost function.

• L2 regularization adds the squared values of the coefficients as penalty term to the cost function.

• L1 regularization can lead to sparse models by forcing some coefficients to be exactly zer...read more
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Q1. What are hyperparameters in random forest
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Hyperparameters in random forest are parameters that are set before the learning process begins.
• Hyperparameters control the behavior of the random forest algorithm.

• They are set by the data scientist and are not learned from the data.

• Examples of hyperparameters in random forest include the number of trees, the maximum depth of trees, and the number of features considered at each split.
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Q2. How to do QnA system with LLM
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A QnA system with LLM is a system that uses the Language Model for Information Retrieval and Question Answering.
• Preprocess the input question and convert it into a format suitable for the LLM model.

• Fine-tune the LLM model on a dataset of question-answer pairs.

• Use the fine-tuned model to generate answers for new questions.

• Evaluate the performance of the QnA system using metrics like precision, recall, and F1 score.

• Itera...read more
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Q3. How to do unit testing
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Unit testing is a process of testing individual units of code to ensure they function correctly.
• Write test cases for each unit of code

• Test inputs, outputs, and edge cases

• Use testing frameworks like JUnit or pytest

• Automate tests to run regularly

• Ensure tests are independent, isolated, and repeatable
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Question related to maths basic and some basic blood relations questions

Q1. All the questions we asked based on the Resume
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Q2. Basic question of program like pattern matching prime number
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Q1. Question on based resume points
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Q2. 2 to 3 codes
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Q3. Project explanation
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Q1. Deep question and answering to know candidature behavior based on Resume
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Q2. Coding in python
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Q3. Project explanation
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Q1. Scenario round, knowing how you think at particular situation
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Q1. Deep discussion about project did in last year. Basics of statistics like regression, hypothesis testing etc. Machine learning algorithms. Python programming basics.
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