InfoSkills Technology Mobile Application Architect Interview Questions, Process, and Tips

Python algorithms: Machine Learning, SQL Questions,

Q1. What is the difference between supervised and unsupervised learning?
Ans. 
Supervised learning uses labeled data to train a model, while unsupervised learning uses unlabeled data to find patterns.
• Supervised learning requires a target variable to be predicted, while unsupervised learning does not.

• Supervised learning algorithms include regression, classification, and decision trees, while unsupervised learning algorithms include clustering and association.

• Examples of supervised learning include...read more
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Q2. How do you build a random forecast model?
Ans. 
A random forecast model can be built using statistical methods and machine learning algorithms.
• Collect and clean the data to be used for the model

• Choose a suitable algorithm for the type of data and problem at hand

• Train the model using the data and algorithm

• Validate the model using a separate set of data

• Adjust the model parameters as needed

• Use the model to make predictions on new data
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Q3. How can you avoid overfitting your model?
Ans. 
To avoid overfitting, use cross-validation, regularization, and increase data size.
• Use cross-validation to test the model on different data sets

• Regularize the model to penalize complex models

• Increase data size to improve the model's ability to generalize

• Use dropout to randomly remove nodes during training

• Use early stopping to prevent the model from overfitting

• Avoid using too many features or variables

• Use simpler models...read more
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Q4. Differentiate between univariate, bivariate, and multivariate analysis.
Ans. 
Univariate analysis deals with one variable, bivariate analysis deals with two variables, and multivariate analysis deals with more than two variables.
• Univariate analysis focuses on describing and analyzing a single variable, such as mean, median, mode, and standard deviation.

• Bivariate analysis examines the relationship between two variables, such as correlation and regression analysis.

• Multivariate analysis involves an...read more
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