Dr. Saumya Chaturvedi

  Theory Syllabus Computer Vision Computer vision is a field of artificial intelligence that deals with how computers can gain high-level understanding from digital images or videos. From the perspective of engineering, it seeks to automate tasks that the human visual system can do. Computer vision tasks include: Object detection:  Identifying and locating objects in an image or video. Object classification:  Determining the category of an object. Scene understanding: Understanding the context of an image or video, such as the location of objects and their relationships to each other. Motion tracking:  Tracking the movement of objects over time. Face recognition:  Identifying and verifying people from their facial features. Computer vision is used in a wide variety of applications, including: Self-driving cars:  Computer vision is used to help self-driving cars see the road, other...

            B.Tech CS/IT  Sem -2   Design & Creativity  (CSP116) Syllabus Lab task 1 Submit here Lab task 2 Submit here

  Syllabus Key types of data analytics Role of ML in Data Science Unit 1 Introduction to ML Assignment 1 Submit here Types of Regression Types of classification Concept of underfitting and overfitting KNN  Decision trees and unsupervised learning  K-Nearest Neighbor(KNN) Algorithm for Machine Learning K-Nearest Neighbour is one of the simplest Machine Learning algorithms based on Supervised Learning technique. K-NN algorithm assumes the similarity between the new case/data and available cases and put the new case into the category that is most similar to the available categories. K-NN algorithm stores all the available data and classifies a new data point based on the similarity. This means when new data appears then it can be easily classified into a well suite category by using K- NN algorithm. K-NN algorithm can be used for Regression as well as for Classification but mostly it is used for the Classification problems. K-NN is a  non-parametric algorithm , which m...