NeoSOFT Jr. Data Scientist Interview Questions and Answers

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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Do well and contribute well

Do well and contribute well

Do well and contribute well

Q1. Why we choose this job
Ans. 
I am passionate about using data to solve complex problems and make meaningful insights.
• I have a strong background in statistics and data analysis

• I enjoy working with large datasets and finding patterns within them

• I am excited about the opportunity to work on real-world problems and make a positive impact
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Q2. What are your expectations
Ans. 
I expect challenging projects, opportunities for growth, supportive team environment, and continuous learning.
• Challenging projects that allow me to apply my skills and knowledge

• Opportunities for growth and advancement within the company

• Supportive team environment where collaboration and knowledge sharing are encouraged

• Continuous learning through training, workshops, and mentorship programs
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Q1. Tell me about your self
Ans. 
I am a data-driven individual with a strong background in statistics and machine learning.
• Graduated with a degree in Statistics

• Proficient in programming languages like Python and R

• Experience with data visualization tools like Tableau

• Completed projects involving predictive modeling and data analysis
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Q2. What are your salary expectations
Ans. 
I am looking for a competitive salary based on my skills and experience.
• Research industry standards for Jr. Data Scientist salaries

• Consider my level of experience and education

• Factor in the cost of living in the area where the job is located
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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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Most like other campus recruiting test

Coding for an example in python

Q1. Query to print date in Sql
Ans. 
Use SELECT statement with DATE_FORMAT function in SQL to print date in desired format.
• Use SELECT DATE_FORMAT(date_column, 'desired_format') FROM table_name;

• Replace 'date_column' with the column containing the date data and 'desired_format' with the format you want to print the date in.

• Example: SELECT DATE_FORMAT(date_column, '%Y-%m-%d') FROM table_name;
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Q2. Question on list and tuple
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Fibonacci series print

Sales dataset to predict future sales

This was good aptitude test computer based

Coding round share screen and code

Q1. Explains OOPs concept
Ans. 
OOPs (Object-Oriented Programming) is a programming paradigm based on the concept of objects, which can contain data and code.
• OOPs focuses on creating objects that interact with each other to solve complex problems.

• Key principles of OOPs include encapsulation, inheritance, polymorphism, and abstraction.

• Encapsulation involves bundling data and methods that operate on the data into a single unit (object).

• Inheritance allo...read more
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Q2. Explain SOLID principles
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SOLID principles are a set of five design principles in object-oriented programming to make software more maintainable, flexible, and scalable.
• Single Responsibility Principle (SRP) - A class should have only one reason to change.

• Open/Closed Principle (OCP) - Software entities should be open for extension but closed for modification.

• Liskov Substitution Principle (LSP) - Objects of a superclass should be replaceable with...read more
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