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I appeared for an interview in Apr 2025, where I was asked the following questions.
The question focuses on coding skills relevant to data science tasks.
Understand data structures: Use arrays, lists, and dictionaries effectively.
Practice algorithms: Implement sorting algorithms like quicksort or mergesort.
Data manipulation: Use libraries like Pandas for data cleaning and transformation.
Model evaluation: Write functions to calculate metrics like accuracy, precision, and recall.
I appeared for an interview in Oct 2024, where I was asked the following questions.
Top trending discussions
LSTM RNN is a type of RNN that can learn long-term dependencies, while simple RNN struggles with vanishing/exploding gradients.
LSTM RNN has more complex architecture with memory cells, input, forget, and output gates.
Simple RNN has a single tanh activation function and suffers from vanishing/exploding gradients.
LSTM RNN is better at capturing long-term dependencies in sequences.
Simple RNN is simpler but struggles with ...
Fine tuning a LLM model involves adjusting hyperparameters to improve performance.
Perform grid search or random search to find optimal hyperparameters
Use cross-validation to evaluate different hyperparameter combinations
Regularize the model to prevent overfitting
Adjust learning rate and batch size for better convergence
Consider using techniques like early stopping to prevent overfitting
I applied via Approached by Company and was interviewed in Nov 2023. There were 2 interview rounds.
DB DC stands for Defined Benefit Defined Contribution, which are types of retirement plans.
DB DC plans are types of retirement plans offered by employers.
Defined Benefit (DB) plans provide a specific benefit upon retirement based on a formula, such as years of service and salary.
Defined Contribution (DC) plans involve contributions from both the employee and employer, with the final benefit depending on the investment ...
I appeared for an interview before Jun 2024, where I was asked the following questions.
I appeared for an interview in Aug 2024.
I appeared for an interview in Jun 2025, where I was asked the following questions.
Developed a predictive model for customer churn using machine learning techniques to enhance retention strategies.
Data Collection: Gathered data from customer interactions, transactions, and feedback.
Data Preprocessing: Cleaned and transformed data, handling missing values and outliers.
Feature Engineering: Created new features like customer tenure and engagement scores to improve model accuracy.
Model Selection: Compare...
I applied via Naukri.com and was interviewed in Aug 2024. There was 1 interview round.
based on 2 interview experiences
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