Machine_Learning

\we are discussion about decision tree which falls under supervised learning algorithm and used for classification and regression both. I Will try to cover to each and every topic regarding this algorithm and write python code to implement the same. before falling to discussion, we need understand this popular technique of machine learning. now the definition is: this tree like structure and a kind of predictive modeling approach. it has tree like structure upside down use to represent decision for decision making. this can handle high dimensional data with high accuracy. this tree also used to predict house price, car value and categorical data as well. the decisoion tree represent root node,terminal node,decision node and branches. sandhyakrishnana decion tree medium

LinearRegression(Simple)  Hello everyone, you reach in good place to understand the machine learning algorithm called linear regression. we will go through each step to complete this topic and starting from basic i.e simple linear regression where we have one input variable only. let's understand with example, suppose we have a business and have to decide how much invest to earn certain amount. or what is value of 3bhk flat or what is car value of 5 years old like that. so, this is generally used to predict the continuous type data. this is simple and commonly  used ML technique or  algorithms based on linear function that we have learned in 10th class or 11th. so lets start with equation now. y=m*x+c (the game is all about this function) y called independent or output or u can say predicted output/actual output. x called input variable or independent variable i.e y value based on x value. m is called slope i.e diff in value of y/diff in value of x c is called i...