Indeed Data Scientist Interview Questions and Answers

Q1. What is clt in statistics
Ans. 
CLT stands for Central Limit Theorem in statistics.
• CLT states that the sampling distribution of the sample mean approaches a normal distribution as the sample size increases.

• It is a fundamental concept in statistics and is used to make inferences about population parameters.

• CLT is important in hypothesis testing, confidence intervals, and regression analysis.

• For example, if you take multiple samples of the same size fr...read more
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Q2. Explain about transformer architecture
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Transformer architecture is a type of neural network architecture commonly used in natural language processing tasks.
• Consists of encoder and decoder layers

• Self-attention mechanism allows for capturing long-range dependencies

• Introduced in the paper 'Attention is All You Need' by Vaswani et al.

• Used in models like BERT, GPT-3, and Transformer-XL
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Q1. Explain about the recent projects that you've done
Ans. 
I have recently worked on a project analyzing customer behavior using machine learning algorithms.
• Utilized clustering algorithms to segment customers based on their purchasing behavior

• Implemented predictive models to forecast customer churn and recommend personalized marketing strategies

• Performed feature engineering to extract meaningful insights from customer data
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Q2. Given a scenario to set up a rag system how would you do it?
Ans. 
Setting up a RAG system involves defining criteria for red, amber, and green statuses to track progress or performance.
• Define clear criteria for red, amber, and green statuses based on key metrics or thresholds.

• Establish a method for regularly monitoring and updating the status of each item or project.

• Communicate the RAG system and its criteria to all stakeholders to ensure understanding and consistency.

• Use visual indi...read more
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You've assigned a task to develop a project. How would you do it?

Q1. Probability ,deep learning basics ,machine learning ,simple python programming questions.
Ans. It will be multilpe choice questions .Duration - 40 minutes.
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Q1. Why this company ,work related to your project,some technical questions on deep learning.
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Q1. Basic ML/DL and statistics questions
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It been for 45 mins. question asked from python,ML,Deep learning and maths.

Q1. 1) explain correlation and convaraince 2) how logistic differ from linear regression
Ans. 
Correlation measures the strength and direction of a linear relationship between two variables, while covariance measures the extent to which two variables change together.
• Correlation ranges from -1 to 1, where 1 indicates a perfect positive relationship, -1 indicates a perfect negative relationship, and 0 indicates no relationship.

• Covariance can be positive, negative, or zero. A positive covariance indicates that as o...read more
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Q1. Basic Recommendation System Questions
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Q2. A B Testing Questions
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Q1. Explain all of decision tree and random forest?
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Decision tree is a tree-like model of decisions and their possible consequences, while random forest is an ensemble learning method that builds multiple decision trees and merges them together.
• Decision tree is a flowchart-like structure where each internal node represents a decision based on an attribute, each branch represents the outcome of the decision, and each leaf node represents a class label.

• Random forest is a ...read more
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Q2. Some basic probability questions
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Q1. Tell me about your projects?
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Q2. How do you approach the project if you are using logistic regression model?
Ans. 
Approach involves data preprocessing, model training, evaluation, and interpretation.
• Perform data preprocessing such as handling missing values, encoding categorical variables, and scaling features.

• Split the data into training and testing sets.

• Train the logistic regression model on the training data.

• Evaluate the model using metrics like accuracy, precision, recall, and F1 score.

• Interpret the model coefficients to under...read more
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Q1. What are you future goals?
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Q2. What would you do if your interested field doesnt have any work in the company?
Ans. 
I would seek opportunities to apply my skills in related fields within the company.
• Explore other departments or teams within the company that may have projects related to my field of interest

• Offer to collaborate with colleagues in different departments to bring a new perspective to their projects

• Seek out professional development opportunities to expand my skills and knowledge in related areas
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