AI Academy #1: Learn Regression Analysis Methods from A-Z
2.7 (8 ratings)
2,096 students enrolled

# AI Academy #1: Learn Regression Analysis Methods from A-Z

Learn Most Important Regression Methods like Linear, Multi-Linear, Polynomial and Logistic Regression
2.7 (8 ratings)
2,096 students enrolled
Created by Sobhan N.
Last updated 11/2018
English
English [Auto-generated]
Current price: \$104.99 Original price: \$149.99 Discount: 30% off
5 hours left at this price!
30-Day Money-Back Guarantee
This course includes
• 4.5 hours on-demand video
• 14 articles
• Access on mobile and TV
• Assignments
• Certificate of Completion
Training 5 or more people?

What you'll learn
• You'll know how Linear Regression work.
• You'll know how Multi Linear Regression work using sklearn and Python.
• Program Logistic Regression from scratch in python.
• Create Regression Model to find global temperature in the next years.
• Build good and accurate Regression Model to estimate advertising campaign sales.
• Build Model to Predict CO2 and Global Temperature by Polynomial Regression.
• Classify Handwritten Images by Logistic Regression
• Classify IRIS Flowers by Logistic Regression
Course content
Expand all 41 lectures 04:21:58
+ Introduction
2 lectures 03:33
Preview 03:25
Required Softwares and Libraries
00:08
+ Linear Regression Analysis
12 lectures 01:11:47
Preview 05:24
Use Linear Regression to Create Model for Random Numbers Part-2
09:38
Source Code
00:12
Learn How to Create Linear Regression Model to Predict Diabetes Part-1
08:13
Learn How to Create Linear Regression Model to Predict Diabetes Part-2
08:17
Source Code
00:13
Linear Regression Model for Boston Houses Data set Part-1
09:34
Linear Regression Model for Boston Houses Data set Part-2
08:32
Source Code
00:11
Linear Regression Model for Built-in Data set
12:33
Source Code
00:09
Linear Regression Analysis Quiz
3 questions
+ Multi Linear Regression
9 lectures 59:48
Multi Linear Regression Theory
07:15
Model Global Temperature Using Multilinear Regression Method Part-1
10:33
Model Global Temperature Using Multilinear Regression Method Part-2
08:48
Source Code
00:16
Make Best Advertising Campaign Using Multilinear Regression Model Part-1
13:25
Make Best Advertising Campaign Using Multilinear Regression Model Part-2
05:25
Source Code
00:16
Multilinear Regression Model for Built-in Dataset
13:35
Source Code
00:14
Multi Linear Regression Analysis Quiz
3 questions
Make multi linear regression model for blob data set .
Multi Linear Regression Assignment
1 question
+ Polynomial Regression Analysis
10 lectures 01:09:03
Polynomial Regression Theory
04:45
Polynomial Regression Model for Sine Function Part-1
12:22
Polynomial Regression Model for Sine Function Part-2
11:00
Source Code
00:30
Learn How to Use Polynomial Regression Model for Built-in Dataset Part-1
07:20
Learn How to Use Polynomial Regression Model for Built-in Dataset Part-2
07:01
Source Code
00:22
Find the Relation between CO2 and Temperature by Polynomial Regression Part-1
11:48
Find the Relation between CO2 and Temperature by Polynomial Regression Part-2
13:15
Source Code
00:39
Polynomial Regression Analysis Quiz
2 questions
Make polynomial regression model for Cosine function.
Polynomial Regression Analysis Assignment
1 question
+ Logistic Regression Analysis
8 lectures 57:45
Logistic Regression Theory
08:17
Use Logistic Regression Model for Blobs Data sets Classification Part-1
08:31
Use Logistic Regression Model for Blobs Data sets Classification Part-2
08:21
Source Code
00:25
Learn How to Use Logistic Regression Model for IRIS Flowers Classification
15:25
Source Code
00:32
Classify Handwritten Digits Using Logistic Regression
15:44
Source Code
00:29
Logistic Regression Analysis Quiz
3 questions
Classify blob data set using logistic regression analysis
Logistic Regression Analysis Assignment
1 question
Requirements
• All you need is a decent PC/Laptop (2GHz CPU, 4GB RAM). You will get the rest from me.
• You should know about basic statistics.
• You must know basic python programming.
• Install Sublime and required library for python.
• You should have a great desire to learn programming and do it in a hands-on fashion, without having to watch countless lectures filled with slides and theory.
Description

In this Course you learn Polynomial Regression & Logistic Regression You learn how to estimate  output of nonlinear system by Polynomial Regressions to find the possible future output Next you go further  You will learn how to classify output of model by using Logistic 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

In the thirdsection you learn how to use python to estimate output of your system. In this section you can estimate output of:

• Nonlinear Sine Function

• Python Dataset

• Temperature and CO2

In the fourth section you learn how to use python to classify output of your system with nonlinear structure .In this section you can estimate output of:

• Classify Blobs

• Classify IRIS Flowers

• Classify Handwritten Digits

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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!

• 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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