American Express
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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
Many Mcq,s.Similar to cat exam
Ml case study . Eg loan default prediction
I applied via Campus Placement and was interviewed before Jul 2023. There were 3 interview rounds.
Medium General Aptitude questions and technical(Big Data, Python etc.)
Understanding deep equations and algorithms in DL and ML is crucial for a data scientist.
Deep learning involves complex neural network architectures like CNNs and RNNs.
Machine learning algorithms include decision trees, SVM, k-means clustering, etc.
Understanding the math behind algorithms helps in optimizing model performance.
Equations like gradient descent, backpropagation, and loss functions are key concepts.
Practica...
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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
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
I was asked Python, sql, coding questions
Case study on how would you identify the total number of footfall on a airport
I applied via Campus Placement
Developed machine learning models to predict customer churn and optimize marketing campaigns.
Built predictive models using Python and scikit-learn
Utilized SQL to extract and manipulate data for analysis
Collaborated with cross-functional teams to implement data-driven solutions
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...
I applied via Company Website and was interviewed before Feb 2023. There was 1 interview round.
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.
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