Data Science Interview Questions & Answers #shorts

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Data Science Interview Questions & Answers

Q: What is data science?
A: Data science is a field of study that uses statistical and computational methods to extract insights and knowledge from data.

Q: What is the difference between supervised and unsupervised learning?
A: Supervised learning is a type of machine learning where the algorithm is trained on labeled data, while unsupervised learning is a type of machine learning where the algorithm is trained on unlabeled data.

Q: What is overfitting?
A: Overfitting occurs when a model is trained too well on the training data, to the point that it begins to memorize the data rather than learn from it. This results in poor performance on new, unseen data.

Q: What is regularization?
A: Regularization is a technique used to prevent overfitting in a model by adding a penalty term to the loss function that encourages simpler models.

Q: What is the curse of dimensionality?
A: The curse of dimensionality refers to the difficulty of analyzing and processing data with a large number of dimensions. As the number of dimensions increases, the amount of data required to accurately represent the space grows exponentially.

Q: What is a decision tree?
A: A decision tree is a tree-like model that represents decisions and their possible consequences, including chance events and the likelihood of different outcomes.

Q: What is the difference between correlation and causation?
A: Correlation is a statistical measure that indicates the extent to which two variables are related. Causation, on the other hand, is a relationship between variables where one variable causes a change in another variable.

Q: What is logistic regression?
A: Logistic regression is a statistical method used for binary classification problems, where the goal is to predict one of two possible outcomes based on input variables.

Q: What is a clustering algorithm?
A: A clustering algorithm is a type of unsupervised learning algorithm that groups similar data points together in clusters based on their characteristics.

Q: What is a recommendation system?
A: A recommendation system is a type of system that uses data and algorithms to suggest items or content that a user might be interested in, based on their past behavior or preferences.

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