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I was interviewed in Dec 2024.
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I applied via Approached by Company and was interviewed before Jul 2023. There was 1 interview round.
MCQ, SQL Programming round --> 1 question , Python programming round --> 1 question, Data Science programming round --> 2 questions
I applied via Approached by Company and was interviewed in Aug 2024. There were 3 interview rounds.
AB testing is a method used to compare two versions of a webpage or app to determine which one performs better.
AB testing involves creating two versions (A and B) of a webpage or app with one differing element
Users are randomly assigned to either version A or B to measure performance metrics
The version that performs better in terms of the desired outcome is selected for implementation
Example: Testing two different call...
It was a classification problem
End to end ML project involves data collection, preprocessing, model training, evaluation, and deployment.
1. Data collection: Gather relevant data from various sources.
2. Data preprocessing: Clean, transform, and prepare the data for modeling.
3. Model training: Develop and train machine learning models using the processed data.
4. Model evaluation: Assess the performance of the models using metrics like accuracy, precis...
I applied via Company Website and was interviewed before May 2020. There were 3 interview rounds.
I applied via Company Website and was interviewed in Jul 2022. There were 3 interview rounds.
Case Study interview
Puzzle
Live Coding
Case study interview
I applied via Referral and was interviewed in Mar 2024. There was 1 interview round.
I applied via Recruitment Consulltant and was interviewed before Jun 2023. There were 2 interview rounds.
I was given assigment on a simple problem where task was to analyse and create a working solution for a problem statement
BERT (Bidirectional Encoder Representations from Transformers) is a pre-trained natural language processing model.
BERT is a transformer-based machine learning algorithm developed by Google.
It is designed to understand the context of words in a sentence by considering both the left and right context simultaneously.
BERT has been pre-trained on a large corpus of text data and can be fine-tuned for specific NLP tasks like ...
Logistic regression is a type of regression analysis used to predict the probability of a binary outcome.
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.
The output of logistic regression is transformed using a sigmoid function to ensure it falls between 0 and 1.
It uses the logistic function to model ...
R-squared value is a statistical measure that represents the proportion of the variance in the dependent variable that is predictable from the independent variable(s).
R-squared value ranges from 0 to 1, with 1 indicating a perfect fit.
It is used to evaluate the goodness of fit of a regression model.
A higher R-squared value indicates that the model explains a larger proportion of the variance in the dependent variable.
F...
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