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JPMorgan Chase & Co.
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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
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
Find second max in list, cal moving avg of a df
I applied via Approached by Company and was interviewed before Sep 2021. There were 3 interview rounds.
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
I applied via Company Website and was interviewed in Dec 2023. There was 1 interview round.
Strong DSA required to crack this Interview
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 Naukri.com and was interviewed in May 2023. There were 2 interview rounds.
Use a regression algorithm like linear regression or decision tree regression.
Consider using linear regression if the relationship between variables is linear.
Decision tree regression can handle non-linear relationships between variables.
Evaluate the performance of different algorithms using cross-validation.
Consider the interpretability of the model when choosing an algorithm.
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