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I applied via Campus Placement and was interviewed in Jan 2024. There were 2 interview rounds.
3 Coding questions were asked
1. Check parenthesis
2. DP
3. Graph
Moderate DSA questions from DP, array and string
I applied via Naukri.com and was interviewed in Jun 2022. There were 3 interview rounds.
I appeared for an interview in Mar 2021.
My current project involves analyzing customer behavior on our e-commerce platform.
Collecting and cleaning data from various sources
Creating visualizations to identify patterns and trends
Using statistical models to make predictions and recommendations
Collaborating with cross-functional teams to implement changes
Tracking and measuring the impact of changes on customer behavior
SQL, Python Coding intermediate questions
Intermediate coding questions
Types of filters include low-pass, high-pass, band-pass, and band-stop filters.
Low-pass filter allows frequencies below a certain cutoff frequency to pass through.
High-pass filter allows frequencies above a certain cutoff frequency to pass through.
Band-pass filter allows a specific range of frequencies to pass through.
Band-stop filter blocks a specific range of frequencies from passing through.
I applied via Referral and was interviewed before Feb 2022. There were 3 interview rounds.
General and basic data structure question
Java programs for strings, palindrome, etc.
Use the StringBuilder class to manipulate strings efficiently.
To check if a string is a palindrome, compare it with its reverse.
To count the occurrences of a substring in a string, use the indexOf method in a loop.
To split a string into an array of substrings, use the split method.
I applied via Walk-in and was interviewed in Feb 2024. There were 3 interview rounds.
Basic Apti , ex train ,speed work
From Leetcode questions
I applied via Recruitment Consultant and was interviewed in Jul 2021. There were 3 interview rounds.
Developed a machine learning model to predict customer churn for a telecom company.
Used logistic regression and decision tree algorithms for classification.
Performed feature engineering to extract relevant features from customer data.
Achieved an accuracy of 85% on the test set.
Provided actionable insights to the company to reduce customer churn.
Different performance metrics are used to measure the effectiveness of a model or system.
Accuracy
Precision
Recall
F1 Score
ROC Curve
AUC
Mean Squared Error
Root Mean Squared Error
R-squared
Bagging and boosting are ensemble learning techniques. XgBoost is a gradient boosting algorithm.
Bagging involves training multiple models on different subsets of the data and combining their predictions.
Boosting involves training models sequentially, with each model trying to correct the errors of the previous model.
XgBoost is an optimized implementation of gradient boosting that uses a combination of tree-based models...
I applied via Campus Placement and was interviewed before Jun 2023. There was 1 interview round.
based on 2 interviews
Interview experience
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