Related Topics Data Science Question 61 Describe the process of cross-validation and its importance in model evaluation? Answer Introduction : Cross-validation is a technique used to evaluate the performance of a machine learning model by testing it on multiple subsets of the data. The basic idea is to split the data into two sets: a […]
Related Topics Data Science Question 58 Describe the process of dimension reduction and its importance in data science? Answer Introduction : Dimension reduction is the process of reducing the number of features (or dimensions) in a dataset while retaining as much relevant information as possible. This is typically done to simplify the dataset, make it
Related Topics Data Science Question 55 Explain the structure of an artificial neural network (ANN)? Answer Introduction: An Artificial Neural Network (ANN) is a machine learning model inspired by the structure and function of the human brain. An ANN consists of interconnected nodes, called neurons, organized in layers. The layers are typically divided into three
Related Topics Data Science Question 52 How imbalanced datasets handle in a binary classification problem in data science? Answer Imbalanced datasets are a common problem in binary classification where one class has significantly more examples than the other. For instance, consider a binary classification problem to detect fraudulent credit card transactions where the number of
Related Topics Data Science Question 48 What are the common data types you work with in data science and how do you handle each of them? Answer Introduction: In data science, there are several common data types that you may encounter, and the way you handle each of them can vary depending on the context
Related Topics Data Science Question 45 What is a variational autoencoder (VAE)? Answer Introduction : A variational autoencoder (VAE) is a type of autoencoder that is used for unsupervised learning, generative modeling, and dimensionality reduction. The VAE is similar to a regular autoencoder, but it uses a probabilistic approach to encode the input data into
Related Topics Data Science Question 42 What is a Kalman filter in data science and its uses? Answer Introduction: In data science, a Kalman filter is a mathematical algorithm that is used to estimate the state of a system based on noisy measurements. It is a recursive algorithm that is particularly useful in applications that
Related Topics Data Science Question 40 What is a Gaussian mixture model (GMM)? Answer Introduction: A Gaussian mixture model (GMM) is a probabilistic model used in data science for clustering and density estimation. The model assumes that the data is generated from a mixture of Gaussian distributions, with each Gaussian component representing a subpopulation of
Related Topics Data Science Question 37 What is the difference between a chi-squared test and a t-test? Answer A t-test and a chi-squared test are both statistical tests that are commonly used in data science. However, they are used to test different types of hypotheses, and they operate on different types of data. A t-test
Related Topics Data Science Question 34 What is the difference between sensitivity and specificity? Answer Sensitivity and specificity are measures used to evaluate the performance of a binary classification model. Sensitivity, also known as recall, is the proportion of true positive cases (i.e., the number of correctly identified positive cases) out of the total number
