This repository contains the task completed under the internship program
Predict the percentage of a student based on the no. of study hours.What will be predicted score if a student studies for 9.25 hrs/ day? In this section we will see how the Python Scikit-Learn library for machine learning can be used to implement regression functions. We will start with simple linear regression involving two variables. Predicting the percentage of marks that a student is expected to score based upon the number of hours they studied. This is a simple linear regression task as it involves just two variables. In this regression task, we will predict the percentage of marks that a student is expected to score based upon the number of hours they studied. This is a simple linear regression task as it involves just two variables.
YouTube link:https://www.youtube.com/watch?v=HGgF8sOPROw
In this section we will see how the Python Scikit-Learn library for machine learning can be used to implement decision tree classifier. We should be able to visualise it graphically. A decision tree is a flowchart-like tree structure where an internal node represents feature(or attribute), the branch represents a decision rule, and each leaf node represents the outcome. The topmost node in a decision tree is known as the root node. It learns to partition on the basis of the attribute value. It partitions the tree in recursively manner call recursive partitioning. This flowchart-like structure helps you in decision making. Based on the feature values given we are going to predict if the Species is iris-versicolor or iris-setosa.
Youtube link:https://www.youtube.com/watch?v=Ngot1tQ3tdc