HSBC Group
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I applied via Referral and was interviewed in Nov 2024. There were 2 interview rounds.
Central Limit Theorem states that the sampling distribution of the sample mean approaches a normal distribution as the sample size increases.
The Central Limit Theorem is essential in statistics as it allows us to make inferences about a population based on a sample.
It states that regardless of the shape of the population distribution, the sampling distribution of the sample mean will be approximately normally distribut...
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I applied via Referral and was interviewed before May 2023. There was 1 interview round.
Feature selection methods help in selecting the most relevant features for building predictive models.
Feature selection methods aim to reduce the number of input variables to only those that are most relevant.
Common methods include filter methods, wrapper methods, and embedded methods.
Examples include Recursive Feature Elimination (RFE), Principal Component Analysis (PCA), and Lasso regression.
HSBC Group interview questions for designations
I applied via Approached by Company and was interviewed before Sep 2021. There were 3 interview rounds.
I applied via Recruitment Consulltant and was interviewed before Aug 2021. There was 1 interview round.
CNN is used for image recognition while MLP is used for general classification tasks.
CNN uses convolutional layers to extract features from images while MLP uses fully connected layers.
CNN is better suited for tasks that require spatial understanding like object detection while MLP is better for tabular data.
CNN has fewer parameters than MLP due to weight sharing in convolutional layers.
CNN can handle input of varying
I applied via LinkedIn and was interviewed in Jul 2024. There were 3 interview rounds.
Assignment on credit risk
Model Gini is a measure of statistical dispersion used to evaluate the performance of classification models.
Model Gini is calculated as twice the area between the ROC curve and the diagonal line (random model).
It ranges from 0 (worst model) to 1 (best model), with higher values indicating better model performance.
A Gini coefficient of 0.5 indicates a model that is no better than random guessing.
Commonly used in credit
XGBoost model is trained by specifying parameters, splitting data into training and validation sets, fitting the model, and tuning hyperparameters.
Specify parameters for XGBoost model such as learning rate, max depth, and number of trees
Split data into training and validation sets using train_test_split function
Fit the XGBoost model on training data using fit method
Tune hyperparameters using techniques like grid search
I was asked Python, sql, coding questions
Case study on how would you identify the total number of footfall on a airport
I was interviewed before Apr 2023.
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