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I applied via Walk-in and was interviewed in Feb 2024. There were 3 interview rounds.
This test was conducted on HackeRank.
It was also conducted on HackeRank.
The project used Angular for the front-end and Node.js for the back-end.
Front-end framework: Angular
Back-end framework: Node.js
API requests are used to communicate with servers to retrieve or send data, typically using HTTP methods.
API requests are made using HTTP methods like GET, POST, PUT, DELETE.
They involve sending a request to a server and receiving a response.
API requests can be used to retrieve data from a server (GET) or send data to a server (POST, PUT, DELETE).
API requests often include headers, parameters, and a request body.
Exampl...
Mostly aptitude questions and problem solving questions.
The tewo coding questions were easy to medium level.
Question related to ML
Technocolabs interview questions for popular designations
I applied via LinkedIn and was interviewed in May 2023. There were 2 interview rounds.
Outliers in a boxplot are defined as data points that fall below Q1 - 1.5*IQR or above Q3 + 1.5*IQR.
Calculate the interquartile range (IQR) by subtracting Q1 from Q3.
Identify the lower bound as Q1 - 1.5*IQR and the upper bound as Q3 + 1.5*IQR.
Any data points below the lower bound or above the upper bound are considered outliers.
For example, if Q1 = 10, Q3 = 20, and IQR = 5, then the lower bound = 10 - 1.5*5 = 2.5 and t
I applied via LinkedIn and was interviewed in Dec 2022. There were 2 interview rounds.
I applied via LinkedIn and was interviewed before Aug 2023. There was 1 interview round.
IQR stands for Interquartile Range, a measure of statistical dispersion.
IQR is calculated as the difference between the 75th percentile (Q3) and the 25th percentile (Q1) of a dataset.
It is used to identify the spread of the middle 50% of the data points in a dataset.
IQR is less sensitive to outliers compared to the range.
Formula: IQR = Q3 - Q1
Missing values can be filled using techniques like mean, median, mode imputation, or advanced methods like regression or machine learning algorithms.
Use mean, median, or mode imputation for numerical data
Use mode imputation for categorical data
Use regression or machine learning algorithms for more complex datasets
I applied via Referral and was interviewed before Apr 2022. There were 3 interview rounds.
Python sql power bi Excel and prepare more on coding
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