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I applied via LinkedIn and was interviewed in Sep 2024. There was 1 interview round.
I applied via Company Website and was interviewed in Apr 2022. There was 1 interview round.
To print a string in Python, use the print() function followed by the string enclosed in quotes.
Use the print() function
Enclose the string in quotes
Use single or double quotes depending on the string
Use escape characters for special characters
To print a string horizontally
Use a loop to iterate through each character of the string
Print each character on the same line using the print() function
HAVING clause is used to filter the results of GROUP BY clause based on a condition.
It is used with GROUP BY clause.
It filters the results based on a condition.
It is used to perform aggregate functions on grouped data.
It is similar to WHERE clause but operates on grouped data.
Views in DBMS are virtual tables that display data from one or more tables.
Views are created using SELECT statements.
They can be used to simplify complex queries.
Views can also be used to restrict access to sensitive data.
They do not store data themselves, but rather display data from other tables.
Changes made to the underlying tables are reflected in the view.
Using HAVING with GROUP function helps filter the results of a GROUP BY query.
HAVING is used to filter the results of a GROUP BY query based on a condition.
It is used after the GROUP BY clause and before the ORDER BY clause.
It is similar to the WHERE clause, but operates on the grouped results rather than individual rows.
Example: SELECT category, COUNT(*) FROM products GROUP BY category HAVING COUNT(*) > 5;
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...
I applied via Naukri.com and was interviewed in Dec 2024. There were 3 interview rounds.
This was good aptitude test computer based
Coding round share screen and code
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...
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...
I applied via Job Fair and was interviewed before Jun 2023. There were 2 interview rounds.
Hackrank coding round of machine learning questions
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...
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...
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
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.
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...
Do well and contribute well
Do well and contribute well
Do well and contribute well
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
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
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
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
I applied via LinkedIn and was interviewed in Nov 2022. There were 2 interview rounds.
Evaluation metrics for multiclass classification
Accuracy
Precision
Recall
F1 Score
Confusion Matrix
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
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.
Fibonacci series print
Sales dataset to predict future sales
I applied via LinkedIn and was interviewed before Feb 2023. There were 2 interview rounds.
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 ...
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