Findability Sciences Senior Data Scientist Interview Questions and Answers

Q1. Technical interview related to my projects and assignments
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Q2. Difference between supervised and unsupervised learning, k means clustering, knn, SQL joins
Ans. 
Supervised learning uses labeled data to train a model, while unsupervised learning uses unlabeled data. K-means clustering is a type of unsupervised learning algorithm. KNN is a supervised learning algorithm. SQL joins are used to combine data from multiple tables.
• Supervised learning uses labeled data to train a model, while unsupervised learning uses unlabeled data

• K-means clustering is a type of unsupervised learning...read more
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Forecasting problem - Predict daily sku level sales

Q1. What is difference between bias and variance
Ans. 
Bias is error due to overly simplistic assumptions, variance is error due to overly complex models.
• Bias is the error introduced by approximating a real-world problem, leading to underfitting.

• Variance is the error introduced by modeling the noise in the training data, leading to overfitting.

• High bias can cause a model to miss relevant relationships between features and target variable.

• High variance can cause a model to ...read more
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Q2. Parametric vs non parametruc model
Ans. 
Parametric models make strong assumptions about the form of the underlying data distribution, while non-parametric models do not.
• Parametric models have a fixed number of parameters, while non-parametric models have a flexible number of parameters.

• Parametric models are simpler and easier to interpret, while non-parametric models are more flexible and can capture complex patterns in data.

• Examples of parametric models inc...read more
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Q1. Related Python Questions on Data Science
Ans. Brush up your knowledge on pandas numpy scikitlearn
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Q1. Technical interview related to my projects and assignments
Add your answer
Q2. Difference between supervised and unsupervised learning, k means clustering, knn, SQL joins
Ans. 
Supervised learning uses labeled data to train a model, while unsupervised learning uses unlabeled data. K-means clustering is a type of unsupervised learning algorithm. KNN is a supervised learning algorithm. SQL joins are used to combine data from multiple tables.
• Supervised learning uses labeled data to train a model, while unsupervised learning uses unlabeled data

• K-means clustering is a type of unsupervised learning...read more
Answered by AI
Add your answer