In this tutorial we will talk in brief about a class of Machine learning problems – Classification Problems. We will try to establish the concept of classification and why they are so important. Continue reading “Introduction to Classification Problems in Machine Learning”
In this tutorial we will learn how to interpret another very important measure called F-Statistic which is thrown out to us in the summary of regression model by R.
This tutorial talks about interpretation of the most fundamental measure reported for models which is R Squared and Adjusted R Squared. We will try to give a clear guidelines for interpreting R Squared and Adjusted R Squared
In this tutorial we will discuss about effectively using diagnostic plots for regression models using R and how can we correct the model by looking at the diagnostic plots.
In this tutorial we will learn a very important aspect of analyzing regression i.e. Residual Analysis. Residual Analysis is a very important tool used by Data Science experts , knowing which will turn you into an amateur to a pro.
Continue reading “R Tutorial : Residual Analysis for Regression”
In this tutorial we will try our hands on a very basic 2 variable linear regression using R. We will also learn how to interpret output given by R and tryout various visualizations required for interpreting simple Linear regression.
In this tutorial we will discuss about structure of Linear regression and how a Linear regression Equation is constructed for 2 variable model.
This tutorial talks about the importance of Testing set and Validation sets for predictive analytic algorithms and different techniques which can be wisely used to get a reliable measure of accuracy.
The tutorial introduces you to the basics of machine learning and different types of machine learning algorithms and how to kick start career in the field of data science by understanding the basics.