Linear & MultiLinear Regression:Artificial Intelligence
Regression techniques for students and professionals. Learn Linear & Multilinear Regression and code them in python
In statistics, Linear Regression is a linear approach for modeling the relationship between a scalar dependent variable Y and one or more explanatory variables (or independent variables) denoted X. The case of one explanatory variable is called simple linear regression. For more than one explanatory variable, the process is called multiple linear regression.
In Linear Regression, the relationships are modeled using linear predictor functions whose unknown model parameters are estimated from the data. Such models are called linear models.
In this Course you learn Linear Regression & Multilinear Regression
You learn how to estimate and predict simple and single variable regression to find the possible future output Next you go further
You will learn how to estimate output of Multivariable model by using Multilinear Regression
In the first section you learn how to use python to estimate output of your system. In this section you can estimate output of:
 Random Number
 Diabetes
 Boston House Price
 Built in Dataset
In the Second section you learn how to use python to estimate output of your system with multivariable inputs.In this section you can estimate output of:
 Global Temprature
 Total Sales of Advertising Campaign
 Built in Dataset
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Your Instructor
Hi! We are UpDegree, providing high quality interactive course.
We are the team of 100+ instructor over the globe. Adel (Oxford), Anand (Standford), Akash (IITB), Rajib (IITK), Partha (IITM) are few of them.
Updegree courses are different, In each and every course you not only get the videos lectures but you also get quiz,code,assignment etc to test your practical understanding!
Course Curriculum

StartIntroduction and Outline (7:22)

StartRequired Softwares and Libraries (4:33)

StartLinear Regression Random Numbers Part1 (8:24)

StartLinear Regression Random Numbers Part2 (7:29)

StartLinear Regression Diabetes Dataset Part1 (5:56)

StartLinear Regression Diabetes Dataset Part2 (5:59)

StartLinear Regression Boston Houses Dataset Part1 (3:28)

StartLinear Regression Boston Houses Dataset Part2 (7:52)

StartLinear Regression Builtin Dataset (1:33)

StartMultilinear Regression Theory (4:45)

StartMultilinear Regression Global Temperature Part1 (11:57)

StartMultilinear Regression Global Temperature Part2 (4:28)

StartMultilinear Regression Global Temperature Part3 (4:05)

StartMultilinear Regression Global Temperature Part4 (4:22)

StartMultilinear Regression Advertising Part1 (14:49)

StartMultilinear Regression Advertising Part2 (3:42)

StartMultilinear Regression Builtin Dataset (1:40)