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I applied via Naukri.com and was interviewed in Apr 2021. There was 1 interview round.
Retesting and regression testing are important testing approaches in SDLC.
Retesting is the process of testing a previously failed test case after the defect has been fixed.
Regression testing is the process of testing the unchanged parts of the software after a change has been made.
Test cases should be written based on requirements and should cover all possible scenarios.
SDLC phases include planning, analysis, design, i
Smoke testing is a preliminary test to check if the basic functionalities of a software application are working fine.
Smoke testing is a subset of regression testing and is usually performed after a build is received.
It is a quick and shallow test to ensure that the critical functionalities of the software are working.
The main purpose of smoke testing is to determine if the build is stable enough for further testing.
If ...
A bug is an error, flaw, mistake, failure, or fault in a computer program or system that causes it to produce incorrect or unexpected results.
A bug can manifest as a software glitch, crash, or malfunction.
Bugs can be caused by coding errors, design flaws, or unexpected interactions between different parts of a system.
Examples of bugs include software freezing, incorrect calculations, and data loss.
Identifying and fixin...
I have extensive knowledge of various tools and their practical applications in consulting projects.
Proficient in using tools like Microsoft Excel, PowerPoint, and Project for data analysis and project management
Familiar with CRM systems like Salesforce for client relationship management
Experience with industry-specific tools like Tableau for data visualization
Ability to adapt and learn new tools quickly to meet projec
I appeared for an interview in Dec 2024.
Bagging and boosting are ensemble learning techniques used to improve the performance of machine learning models by combining multiple weak learners.
Bagging (Bootstrap Aggregating) involves training multiple models independently on different subsets of the training data and then combining their predictions through averaging or voting.
Boosting involves training multiple models sequentially, where each subsequent model c...
Overfitting is when a model learns the training data too well, leading to poor performance on new, unseen data.
Overfitting occurs when a model is too complex and captures noise in the training data.
It can be mitigated by using techniques like cross-validation, regularization, and early stopping.
Examples of overfitting include a decision tree with too many branches or a neural network with too many hidden layers.
Discrete variables can only take specific values, while continuous variables can take any value within a range.
Discrete variables are countable and have distinct values, such as number of students in a class.
Continuous variables can take any value within a range, such as height or weight.
Discrete variables are often represented by integers, while continuous variables are represented by real numbers.
I applied via LinkedIn and was interviewed in Nov 2024. There were 2 interview rounds.
I applied via Approached by Company and was interviewed in Feb 2023. There were 2 interview rounds.
I applied via Approached by Company and was interviewed in Oct 2022. There were 3 interview rounds.
General computer knowledge test
Program writing in computer basic ideas
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