iMentus Interview Questions, Process, and Tips

It was an half hour test 20 questions purely based on ML and statistical knowledge.

Q1. ML techniques, statistics behind them and questions about your project
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Q1. What is precision and recall
Ans. 
Precision and recall are evaluation metrics used in machine learning to measure the performance of a classification model.
• Precision is the ratio of correctly predicted positive observations to the total predicted positive observations.

• Recall is the ratio of correctly predicted positive observations to the all observations in actual class.

• Precision is important when the cost of false positives is high, while recall is i...read more
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Q1. What are the different supervised models used
Ans. 
Supervised models include linear regression, logistic regression, decision trees, random forests, support vector machines, and neural networks.
• Linear regression: used for predicting continuous outcomes

• Logistic regression: used for binary classification

• Decision trees: used for classification and regression tasks

• Random forests: ensemble method using multiple decision trees

• Support vector machines: used for classification ...read more
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Q2. Linear regression, logistic regression, decision tree
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Q1. What are the salary expectations
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Q1. Evaluation metrics used in multiclass classification
Ans. 
Evaluation metrics for multiclass classification
• Accuracy

• Precision

• Recall

• F1 Score

• Confusion Matrix
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Q2. Difffereence between append and extend
Ans. 
Append adds a single element to a list while extend adds multiple elements.
• Append adds the element as it is to the end of the list.

• Extend takes an iterable and adds each element of the iterable to the end of the list.

• Append can be used to add a single element to a list.

• Extend can be used to add multiple elements to a list.

• Example: list1 = [1, 2, 3], list2 = [4, 5], list1.append(4) will result in [1, 2, 3, 4], list1.ext
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Q3. Sort a list and take out second minimum
Ans. 
Sort a list and extract the second minimum value.
• Sort the list in ascending order using the sort() method.

• Extract the second minimum value using indexing.

• Handle cases where the list has less than two elements.
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Q1. Introduction and overview of the projects
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Q1. Computer vision questions
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Hackrank coding round of machine learning questions

Q1. What is logistic regression
Ans. 
Logistic regression is a statistical model used to predict the probability of a binary outcome based on one or more predictor variables.
• Logistic regression is used when the dependent variable is binary (e.g., 0 or 1, yes or no).

• It estimates the probability that a given input belongs to a certain category.

• It uses the logistic function to model the relationship between the dependent variable and independent variables.

• Coe...read more
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Q2. What is linear 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 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 repres...read more
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Q3. What experince do you have in model deployment
Ans. 
I have experience deploying machine learning models using cloud services like AWS SageMaker and Azure ML.
• Deployed a sentiment analysis model on AWS SageMaker for real-time predictions

• Deployed a recommendation system model on Azure ML for batch predictions

• Used Docker containers to deploy models in production environments
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Q4. What are transformers ?
Ans. 
Transformers are models used in natural language processing (NLP) that learn contextual relationships between words.
• Transformers use self-attention mechanisms to weigh the importance of different words in a sentence.

• They have revolutionized NLP tasks such as language translation, sentiment analysis, and text generation.

• Examples of transformer models include BERT, GPT-3, and RoBERTa.
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Q5. What is hyperparameter tuning
Ans. 
Hyperparameter tuning is the process of selecting the best set of hyperparameters for a machine learning model.
• Hyperparameters are parameters that are set before the learning process begins, such as learning rate, number of hidden layers, etc.

• Hyperparameter tuning involves trying out different combinations of hyperparameters to find the ones that result in the best model performance.

• Techniques for hyperparameter tuning...read more
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Normal there is not advance requirment

Q1. Will you work will less amount package
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Q2. You wouldn't get any travel cost?
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Q3. What about machine learning
Ans. 
Machine learning is a branch of artificial intelligence that focuses on developing algorithms and models that can learn from and make predictions or decisions based on data.
• Machine learning involves training algorithms to learn patterns from data and make predictions or decisions.

• It can be supervised, unsupervised, or semi-supervised learning.

• Examples include recommendation systems, image recognition, and natural langu
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Q4. Tellm me about any cloud platform
Ans. 
A cloud platform is a service that allows users to store, manage, and process data remotely.
• Cloud platforms provide scalable and flexible storage solutions

• They offer various services such as computing power, databases, and analytics tools

• Examples include Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform
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Q5. Telll me about pointer
Ans. 
A pointer is a variable that stores the memory address of another variable.
• Pointers are used to access and manipulate memory directly.

• They are commonly used in programming languages like C and C++.

• Example: int *ptr; // declaring a pointer variable
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