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Wells Fargo
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Basic sql and tableau questions, easy I would say
I have 8 years of experience in data science, with a focus on machine learning and predictive modeling.
8 years of experience in data science
Specialize in machine learning and predictive modeling
Worked on various projects involving big data analysis
Experience with programming languages such as Python and R
I have worked on developing machine learning models for predictive maintenance in the manufacturing industry.
Developed machine learning algorithms to predict equipment failures in advance
Utilized sensor data and historical maintenance records to train models
Implemented predictive maintenance solutions to reduce downtime and maintenance costs
posted on 18 May 2023
I applied via Approached by Company and was interviewed before May 2022. There were 2 interview rounds.
I applied via Referral and was interviewed in Nov 2024. There were 2 interview rounds.
posted on 14 Jun 2024
I applied via Referral and was interviewed in May 2024. There was 1 interview round.
Linear regression is a statistical method used to model the relationship between a dependent variable and one or more independent variables.
Collect data on the variables of interest
Plot the data to visualize the relationship between the variables
Choose a suitable linear regression model (simple or multiple)
Fit the model to the data using a regression algorithm (e.g. least squares)
Evaluate the model's performance using ...
Linear Regression minimizes noise by fitting a line that best represents the relationship between variables.
Linear Regression minimizes the sum of squared errors between the actual data points and the predicted values on the line.
It assumes that the noise in the data is normally distributed with a mean of zero.
Outliers in the data can significantly impact the regression line and its accuracy.
Regularization techniques l...
Use linear algebra to solve for coefficients in two equations.
Set up the two equations with unknown coefficients
Solve the equations simultaneously using methods like substitution or elimination
Example: 2x + 3y = 10 and 4x - y = 5, solve for x and y
I have 8 years of experience in data science, with a focus on machine learning and predictive modeling.
8 years of experience in data science
Specialize in machine learning and predictive modeling
Worked on various projects involving big data analysis
Experience with programming languages such as Python and R
I have worked on developing machine learning models for predictive maintenance in the manufacturing industry.
Developed machine learning algorithms to predict equipment failures in advance
Utilized sensor data and historical maintenance records to train models
Implemented predictive maintenance solutions to reduce downtime and maintenance costs
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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