Ace your CBSE boards with these Classification Algorithm-2 MCQs — fully exam-oriented, covering all topics, designed to boost concepts and maximize your score. Q1. The K-Nearest Neighbors (K-NN) algorithm belongs to which category of machine learning? a) Unsupervised Learning b) Supervised Learning c) Reinforcement Learning d) Semi-supervised Learning Show Answer Answer: b) Supervised Learning Q2….
Practice high-quality, exam-oriented Classification Algorithm-1 MCQs to strengthen your concepts, crack the CBSE question pattern, and walk into exam fully prepared. Q1. What is a Decision Tree? a) A statistical regression formula b) A diagrammatic representation of the decision-making process with a tree-like structure c) A type of neural network d) A clustering algorithm Show…
Exploratory Data Analysis MCQs built to ace your score — exam-oriented questions covering every topic in the CBSE Class 12 Data Science syllabus with zero gaps. Q1. Which of the following best describes Exploratory Data Analysis (EDA)? a) A process of building machine learning models b) A process of carrying out an initial analysis of…
Practice high-quality Data Governance MCQs to strengthen concepts, understand the CBSE question pattern, and boost your confidence for the exam. Q1. Which of the following best describes Data Governance? a) A method of storing data only b) A collection of people, technologies, processes and policies for managing and protecting data c) A technique used only…
Get Unsupervised Learning Notes specially desinged for Data Science students of Class 12 as per CBSE latest Curriculum. Introduction to Unsupervised Learning Real-World Applications of Unsupervised Learning Introduction to Clustering K-Means Clustering
Regression Algorithms-2 Notes deals with Multiple Linear Regression and Non-Linear Regression. It is aligned with CBSE Class 12 DS Syllabus and pointwise notes. Multiple Linear Regression Non-Linear Regression
In this Regression Algorithms-1 Notes, You learn Linear Regression, Mean Absolute Error(MAE), and Root Mean Square Deviation (RMSD). This is designed for Class 12 DS students and based on latest CBSE curriculum. Introduction to Linear Regression Mean Absolute Error (MAE) Root Mean Square Deviation (RMSD)
Classification Algorithms-2 Notes of Class 12 DS covers K-Nearest Neighbors (K-NN), its characteristics, advantages, disadvantages, and Cross Validation. Introduction to K-Nearest Neighbors (K-NN) Characteristics of K-Nearest Neighbors (K-NN) Advantages of K-NN Disadvantages of K-NN Cross Validation
Classification Algorithm-1 Notes for Class 12 Data Science (CBSE) covering Decision Trees, their applications, and steps to create them with easy, pointwise explanations. Introduction to Decision Trees Applications of Decision Trees Decision Trees for Classification and Regression Creating a Decision Tree Steps to Create a Decision Tree
In these Exploratory Data Analysis Notes for Class 12 DS (CBSE), you’ll learn about EDA, Univariate Analysis, Bivariate Analysis, Multivariate Analysis, Graphical Analysis, and Clustering with simple, pointwise notes prepared as per the latest CBSE curriculum. Introduction to Exploratory Data Analysis (EDA) Univariate Analysis Bivariate Analysis Multivariate Analysis Data Cleaning Steps of Data Cleaning