Artificial Intelligence #1: Linear & MultiLinear Regression

Regression techniques for students and professionals. Learn Linear & Multilinear Regression and code them in python

3.95 (29 reviews)
Udemy
platform
English
language
Data Science
category
instructor
Artificial Intelligence #1: Linear & MultiLinear Regression
3,165
students
2.5 hours
content
Sep 2018
last update
$19.99
regular price

What you will learn

Program Linear Regression from scratch in python.

Program Multilinear Regression from scratch in python.

Predict output of model easily and precisely.

Use Regression model to solve real world problems.

Create Regression Model to find global temperature in the next years.

Build good and accurate Regression Model to estimate advertising campaign sales.

Description

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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Important information before you enroll:

  • In case you find the course useless for your career, don't forget you are covered by a 30 day money back guarantee, full refund, no questions asked!

  • Once enrolled, you have unlimited, lifetime access to the course!

  • You will have instant and free access to any updates I'll add to the course.

  • You will give you my full support regarding any issues or suggestions related to the course.

  • Check out the curriculum and FREE PREVIEW lectures for a quick insight.

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It's time to take Action!

Click the "Take This Course" button at the top right now!

...Don't waste time! Every second of every day is valuable...

I can't wait to see you in the course!

Best Regrads,

Sobhan





Content

Introduction

Introduction
Required Softwares and Libraries

Linear Regression

Linear Regression Theory
Linear Regression Random Numbers Part-1
Linear Regression Random Numbers Part-2
Linear Regression Random Numbers Source
Linear Regression Diabetes Dataset Part-1
Linear Regression Diabetes Dataset Part-2
Linear Regression Diabetes Dataset Source
Linear Regression Boston Houses Dataset Part-1
Linear Regression Boston Houses Dataset Part-2
Linear Regression Boston Houses Dataset Source
Linear Regression Built-in Dataset
Linear Regression Built-in Dataset Source

Multilinar Regression

Multilinear Regression Theory
Multilinear Regression Global Temperature Part-1
Multilinar Regression Global Temperature Part-2
Multilinear Regression Global Temperature Source
Multilinear Regression Advertising Part-1
Multilinear Regression Advertising Part-2
Multilinear Regression Advertising Source
Multilinear Regression Built-in Dataset
Multilinear Regression Built-in Dataset Source

Reviews

Tharindu
July 13, 2019
This course is amazing and above my expectations! Very good exercises, good speed, well communicated. The instructor made me feel very comfortable and was able to take many things away. Excellent content and very knowledgeable instructor!
Zaied
August 29, 2018
Having a very good learning experience. Contents are concise and practical problem oriented. Instructor is experienced and knows what he's doing. Looking forward to learn more from similar courses.
Sina
November 19, 2017
very good course about regression that i found on udemy. This course is very practical and helpful about linear and multi linear regression.
Fazi
November 18, 2017
This course is really good instructor send content clearly and simply. I appreciate the pace of learning. content are easy to understand. I highly recommend it.

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1435762
udemy ID
11/16/2017
course created date
11/21/2019
course indexed date
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