Chapter D - Data Science [CSCI101-] Questions and Answers 100% Pass

Chapter D - Data Science [CSCI101-] Questions and Answers 100% Pass What does "data preprocessing" involve in data science? Cleaning and transforming raw data into a usable format for analysis. Which programming language is widely used in data science for statistical analysis? R. What is the role of machine learning in data science? To develop models that can make predictions or decisions based on data. What is the difference between supervised and unsupervised learning? Supervised learning uses labeled data for training, while unsupervised learning uses unlabeled data to find patterns. What does "feature selection" mean in data science? Choosing the most relevant variables for building a predictive model. 2 What is a dataset in the context of data science? A collection of data points, typically organized in rows and columns. What is the purpose of data visualization in data science? To represent data graphically for easier interpretation and insights. What is the significance of "Big Data" in data science? It refers to large, complex datasets that traditional data processing tools cannot handle efficiently. What is an example of a classification problem in data science? Predicting whether an email is spam or not based on its content. What is a correlation in statistics? A measure of the relationship between two variables. What is overfitting in a machine learning model? 3 When a model learns the details of the training data too well, leading to poor performance on new, unseen data. What is the purpose of "cross-validation" in machine learning? To evaluate a model's performance by testing it on multiple subsets of data. What is the function of a "decision tree" in machine learning? To model decisions and their possible consequences using a tree-like structure. What does "accuracy" measure in a classification model? The proportion of correct predictions made by the model. What is the difference between "regression" and "classification" in machine learning? Regression predicts continuous values, while classification predicts discrete labels or categories. What is a "confusion matrix" used for in evaluating machine learning models? 4 It is used to summarize the performance of a classification algorithm by showing true positives, true negatives, false positives, and