Support Vector Machine- A beginner overview

<p>Today’s topic is Support Vector Machines (SVM), a concept in Machine Learning widely used for tasks like image and text classification, as well as face detection. SVM falls under the category of Supervised Learning in Machine Learning. In Supervised Learning, we teach the computer to recognize patterns in data, and it uses those patterns to make predictions about new, unseen data. In the case of SVM, we train the computer with past data, and it learns from that training to make predictions about future data.</p> <h1>Working</h1> <p>To illustrate how SVM works, imagine you want to classify people into two teams: “Mr. India,” consisting of individuals wearing red uniforms, and “Mogambo,” consisting of people wearing black uniforms. You’ve trained your computer with data of people in these two teams based on their attire. Now, when a new person appears, the SVM model will analyze their attire and place them either in “Team Mr. India” or “Team Mogambo.”</p> <p>SVM model acts in a similar fashion but in a more mathematical way. It finds the best line that separates the two classes (in this case, the teams), ensuring that the distance between this line and the nearest data points from both teams is maximized.</p> <p><a href="https://medium.com/@anjanakrishnan3100/support-vector-machine-a-beginner-overview-70579ca708ce">Read More</a></p>