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I applied via LinkedIn and was interviewed in Jul 2024. There were 3 interview rounds.
Assignment on credit risk
Python coding question and ML question
Use string manipulation to efficiently extract numbers before the decimal point from a list of decimal numbers.
Split each decimal number by the decimal point and extract the number before it
Use regular expressions to match and extract numbers before the decimal point
Iterate through the list and extract numbers using string manipulation functions
Softmax and sigmoid are both activation functions used in neural networks.
Softmax is used for multi-class classification problems, while sigmoid is used for binary classification problems.
Softmax outputs a probability distribution over the classes, while sigmoid outputs a probability for a single class.
Softmax ensures that the sum of the probabilities of all classes is 1, while sigmoid does not.
Softmax is more sensitiv...
Wells Fargo interview questions for designations
posted on 7 May 2024
I applied via Job Portal and was interviewed in Nov 2023. There was 1 interview round.
Gradient descent is an optimization algorithm used to minimize a function by iteratively moving in the direction of steepest descent.
Gradient descent is used to find the minimum of a function by taking steps proportional to the negative of the gradient at the current point.
It is commonly used in machine learning to optimize the parameters of a model by minimizing the loss function.
There are different variants of gradie...
LSTM (Long Short-Term Memory) is a type of recurrent neural network designed to handle long-term dependencies.
LSTM has three gates: input gate, forget gate, and output gate.
Input gate controls the flow of information into the cell state.
Forget gate decides what information to discard from the cell state.
Output gate determines the output based on the cell state.
T-test is a statistical test used to determine if there is a significant difference between the means of two groups.
Mean is the average of a set of numbers, median is the middle value when the numbers are ordered, and mode is the most frequently occurring value.
Mean is sensitive to outliers, median is robust to outliers, and mode is useful for categorical data.
T-test is used to compare means of two groups, mean is used...
Random Forest is an ensemble learning method used for classification and regression tasks.
Random Forest is a collection of decision trees that are trained on random subsets of the data.
Each tree in the forest makes a prediction, and the final prediction is the average (regression) or majority vote (classification) of all trees.
Random Forest helps reduce overfitting and improve accuracy compared to a single decision tre...
posted on 20 Jun 2024
I applied via IIM Jobs and was interviewed before Jun 2023. There was 1 interview round.
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 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.
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...
I applied via Referral and was interviewed in Nov 2024. There were 2 interview rounds.
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