Kumarans Data Academy

Regression models are a type of machine learning model used to predict. It tries to find a relationship between columns.  Regression Models are ready-made mathematical formulas created to make life easier . 1. Linear Regression: Linear Regression is a model that checks whether there is a relationship between two or more columns. The relationship means: if one column value increases, will the other column value also increase or decrease. If you study more hours, your marks will increase. If you have more work experience, your salary will increase. These are called positive relationships. Example: Students Mark - It can change over time, It is a Numerical score. Sales - It can change over time, It is a Numerical Count. Temperature - It can change over time. It is Number based. Here is a Simple Linear Regression Graph: If you have a Students Marks & Study time data for past 1 year, you can predict future marks using Linear Regression. 2. Logistic Regression: It is used for Pr...

Prediction - Finding out what will happen in Future. It may not be 100% Exact. But At least you know something is more likely to happen, with the help of prediction Analysis. This is called Predictive Analysis . One of the four important Types of Analysis. If you have last 10 months of students mark data, you can do predictive analysis and find future marks of the students. Why Predictive Analysis is Useful in Real Jobs? Sales Department : To Predict next month’s Profit, Sales, Product preference. Marketing Department : To Predict which customer is likely to buy a product. HR Department : To Predict which employee may leave the company in upcoming months. Education Sector : To Predict student performance and give early support before exams. Healthcare : To Predict patient risk level or future disease based on historic records. Government: To Predict Future Population Growth, Future Economy Level, Future Demands, Future Employment and business growth. Military: To Predict threats, Ear...