Polynomial Regression is a regression algorithm that models the relationship between a dependent(y) and independent variable(x) as nth degree polynomial. The Polynomial Regression equation is given below: y= b0+b1x1+ b2x12+ b2x13+…… bnx1n It is also called the special case of Multiple Linear Regression in ML. Because we add some polynomial terms to the Multiple Linear… Continue reading ML Polynomial Regression
Month: April 2022
What is Backward Elimination?
Backward elimination is a feature selection technique while building a machine learning model. It is used to remove those features that do not have a significant effect on the dependent variable or prediction of output. There are various ways to build a model in Machine Learning, which are: All-in Backward Elimination Forward Selection Bidirectional Elimination… Continue reading What is Backward Elimination?
Multiple Linear Regression
In the previous topic, we have learned about Simple Linear Regression, where a single Independent/Predictor(X) variable is used to model the response variable (Y). But there may be various cases in which the response variable is affected by more than one predictor variable; for such cases, the Multiple Linear Regression algorithm is used. Moreover, Multiple… Continue reading Multiple Linear Regression
Simple Linear Regression in ML
Simple Linear Regression is a type of Regression algorithms that models the relationship between a dependent variable and a single independent variable. The relationship shown by a Simple Linear Regression model is linear or a sloped straight line, hence it is called Simple Linear Regression. The key point in Simple Linear Regression is that the dependent… Continue reading Simple Linear Regression in ML
Linear Regression in Machine Learning
Linear regression is one of the easiest and most popular Machine Learning algorithms. It is a statistical method that is used for predictive analysis. Linear regression makes predictions for continuous/real or numeric variables such as sales, salary, age, product price, etc. Linear regression algorithm shows a linear relationship between a dependent (y) and one or more independent… Continue reading Linear Regression in Machine Learning
Regression Analysis in Machine learning
Regression analysis is a statistical method to model the relationship between a dependent (target) and independent (predictor) variables with one or more independent variables. More specifically, Regression analysis helps us to understand how the value of the dependent variable is changing corresponding to an independent variable when other independent variables are held fixed. It predicts… Continue reading Regression Analysis in Machine learning
How to get datasets for Machine Learning
The key to success in the field of machine learning or to become a great data scientist is to practice with different types of datasets. But discovering a suitable dataset for each kind of machine learning project is a difficult task. So, in this topic, we will provide the detail of the sources from where… Continue reading How to get datasets for Machine Learning
Difference b/w AI and ML
Artificial intelligence and machine learning are the part of computer science that are correlated with each other. These two technologies are the most trending technologies which are used for creating intelligent systems. Although these are two related technologies and sometimes people use them as a synonym for each other, but still both are the two… Continue reading Difference b/w AI and ML
Installing Anaconda and Python
To learn machine learning, we will use the Python programming language in this tutorial. So, in order to use Python for machine learning, we need to install it in our computer system with compatible IDEs (Integrated Development Environment). In this topic, we will learn to install Python and an IDE with the help of Anaconda distribution. Anaconda… Continue reading Installing Anaconda and Python
Machine learning Life cycle
Machine learning has given the computer systems the abilities to automatically learn without being explicitly programmed. But how does a machine learning system work? So, it can be described using the life cycle of machine learning. Machine learning life cycle is a cyclic process to build an efficient machine learning project. The main purpose of… Continue reading Machine learning Life cycle