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I applied via Approached by Company and was interviewed before May 2023. There were 4 interview rounds.
I chose this ML model because of its high accuracy and interpretability.
The chosen model has shown superior performance in cross-validation compared to other models.
The model's interpretability allows for easier understanding of feature importance and decision-making processes.
The chosen model is well-suited for the specific problem domain and dataset characteristics.
For example, I chose a Random Forest model over a Ne...
Shap values explain individual predictions in machine learning models.
Shap values quantify the impact of each feature on a model's predictions.
They help in understanding the importance of different features in the model.
Shap plots visually represent the impact of features on predictions.
They can be used to explain black-box models like XGBoost or neural networks.
Tree based models use decision trees to make predictions, with hyperparameters controlling the model's behavior.
Tree based models are a type of machine learning model that uses decision trees to make predictions.
Hyperparameters are settings that control the behavior of the model, such as the maximum depth of the tree or the minimum number of samples required to split a node.
Examples of tree based models include Random
Pharma case study questions
Top trending discussions
I applied via Recruitment Consulltant and was interviewed in Apr 2024. There were 3 interview rounds.
I applied via Approached by Company and was interviewed in Mar 2024. There were 5 interview rounds.
MLOps focuses on machine learning model deployment and management, while DevOps focuses on software development and IT operations.
MLOps is specifically tailored for machine learning models, ensuring they are deployed, monitored, and managed effectively.
DevOps is a broader practice that focuses on collaboration between development and operations teams to automate and streamline the software development process.
MLOps inc...
Explode function in Python is used to split a string into a list of strings based on a specified delimiter.
Use the explode function from the pandas library to split a string column into multiple rows in a DataFrame.
Specify the delimiter parameter to define how the string should be split.
For example, df['column'].str.split('delimiter').explode() will split the strings in 'column' based on 'delimiter' and create a new ro
I applied via Approached by Company and was interviewed in Oct 2024. There were 2 interview rounds.
Combination logic on python
Classification is a machine learning technique used to categorize data into different classes or categories based on past observations.
Classification involves training a model on labeled data to predict the class of new, unseen data points.
Common algorithms for classification include logistic regression, decision trees, support vector machines, and k-nearest neighbors.
Examples of classification tasks include spam email...
Machine Learning, Metrics
I applied via Approached by Company and was interviewed before May 2023. There were 2 interview rounds.
Beta value in logistic regression measures the impact of independent variables on the log odds of the dependent variable.
Beta value indicates the strength and direction of the relationship between the independent variables and the log odds of the dependent variable.
A positive beta value suggests that as the independent variable increases, the log odds of the dependent variable also increase.
A negative beta value sugges...
1. You are the data scientist of a digital store. You have to recommend top 10 products to a customer. What variables and techniques will you use to recommend the top 10 products?
I applied via Approached by Company and was interviewed before Sep 2023. There were 3 interview rounds.
Simple Data Science Case Study
Data Science Case Study
I applied via Referral and was interviewed in Mar 2024. There was 1 interview round.
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