Acmegrade Data Scientist Interview Questions and Answers

Q1. Tell me about yourself
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Q2. Questions from projects which was mentioned on resume
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Q1. Fitment based questions
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Q2. Explain a project
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Developed a machine learning model to predict customer churn for a telecom company.
• Collected and cleaned customer data including usage patterns and demographics

• Used classification algorithms like Random Forest and Logistic Regression to build the model

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

Q1. Asked me about expected salary
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Q1. What is difference between lstm and rnn
Ans. 
LSTM is a type of RNN that addresses the vanishing gradient problem by using memory cells.
• RNN stands for Recurrent Neural Network, a type of neural network that processes sequential data.

• LSTM stands for Long Short-Term Memory, a type of RNN that includes memory cells to retain information over long sequences.

• LSTM is designed to overcome the vanishing gradient problem, which occurs when training RNNs on long sequences.

• L...read more
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Q1. What are different evaluation matrix ?
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Evaluation matrices are used to assess the performance of models in data science.
• Confusion matrix: used to evaluate the performance of classification models.

• Precision, recall, and F1 score: measures for binary classification models.

• Mean squared error (MSE): evaluates the performance of regression models.

• R-squared: assesses the goodness of fit for regression models.

• Area under the ROC curve (AUC-ROC): evaluates the perfo...read more
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Q1. What is linear regression? How to process data? Explain KLM algorithm.
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Linear regression is a statistical method used to model the relationship between a dependent variable and one or more independent variables.
• Linear regression is used to predict the value of a dependent variable based on the value of one or more independent variables.

• It assumes a linear relationship between the independent and dependent variables.

• The goal of linear regression is to find the best-fitting line that minimi...read more
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Mostly around generative ai , transformer

Q1. Where do you yourself in next 5 years?
Ans. 
In the next 5 years, I see myself advancing my skills in data science, taking on more leadership roles, and contributing to impactful projects.
• Continuing to enhance my knowledge in machine learning algorithms and data visualization techniques

• Leading a team of data scientists on complex projects

• Contributing to projects that have a positive impact on society, such as healthcare analytics or environmental sustainability

• Po...read more
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Q2. How do you handle tough situation ?
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I handle tough situations by staying calm, analyzing the problem, seeking advice if needed, and taking decisive action.
• Stay calm and composed

• Analyze the problem thoroughly

• Seek advice from colleagues or mentors

• Take decisive action to address the situation
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Aptitude tests measure a person's logical reasoning skills and mental ability. During an aptitude test, test-takers must answer questions designed to assess their diagrammatic reasoning, mechanical reasoning, numerical reasoning and verbal reasoning skills.they test your ability,time management and accuracy during test ..

Awareness of Topics Relating to Your Background Is Crucial.
The most thought-provoking way to start a group discussion is to ask a question or add a famous and relevant quote to the topic. You can simply grab the attention of everyone as an initiator and thus lead a powerful group discussion by using a question on the topic.

Q1. Attended the interview on April 2023. 2 panel members joined the interview. Most of the questions are from basic ML and DL concepts. Same day I received the documents upload email and had salary discussio...read more
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Q2. What is activation function? Explain Naive Bayes? Confusion matrix? Hyperparameters in DL? Hypothesis testing
Ans. 
Activation function is a mathematical function used in neural networks to introduce non-linearity.
• Activation function is applied to the weighted sum of inputs in a neural network node.

• It helps in determining the output of a node or the activation of a neuron.

• Common activation functions include sigmoid, tanh, ReLU, and softmax.

• Activation functions introduce non-linearity, allowing neural networks to learn complex patter...read more
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Q1. What are your projects Explain one in brief
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Q1. Knn and logistic regression
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Q2. Correlation vs covariance
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Covariance measures the relationship between two variables, while correlation measures the strength and direction of the relationship.
• Covariance can be positive, negative, or zero, indicating the direction of the relationship between variables.

• Correlation is always between -1 and 1, with 1 indicating a perfect positive relationship, -1 indicating a perfect negative relationship, and 0 indicating no relationship.

• Covaria...read more
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