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Published on April 16, 2017 by Edureka
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This Edureka Linear Regression tutorial will help you understand all the basics of linear regression machine learning algorithm along with examples. This tutorial is ideal for both beginners as well as professionals who want to learn or brush up their Data Science concepts. Below are the topics covered in this tutorial:

1) Introduction to Machine Learning
2) What is Regression?
3) Types of Regression
4) Linear Regression Examples
5) Linear Regression Use Cases
6) Demo in R: Real Estate Use Case

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#LinearRegression #Datasciencetutorial #Datasciencecourse #datascience

How it Works?

1. There will be 30 hours of instructor-led interactive online classes, 40 hours of assignments and 20 hours of project
2. We have a 24×7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course.
3. You will get Lifetime Access to the recordings in the LMS.
4. At the end of the training you will have to complete the project based on which we will provide you a Verifiable Certificate!

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About the Course

Edureka’s Data Science course will cover the whole data life cycle ranging from Data Acquisition and Data Storage using R-Hadoop concepts, Applying modelling through R programming using Machine learning algorithms and illustrate impeccable Data Visualization by leveraging on ‘R’ capabilities.

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Why Learn Data Science?

Data Science training certifies you with ‘in demand’ Big Data Technologies to help you grab the top paying Data Science job title with Big Data skills and expertise in R programming, Machine Learning and Hadoop framework.

After the completion of the Data Science course, you should be able to:
1. Gain insight into the ‘Roles’ played by a Data Scientist
2. Analyse Big Data using R, Hadoop and Machine Learning
3. Understand the Data Analysis Life Cycle
4. Work with different data formats like XML, CSV and SAS, SPSS, etc.
5. Learn tools and techniques for data transformation
6. Understand Data Mining techniques and their implementation
7. Analyse data using machine learning algorithms in R
8. Work with Hadoop Mappers and Reducers to analyze data
9. Implement various Machine Learning Algorithms in Apache Mahout
10. Gain insight into data visualization and optimization techniques
11. Explore the parallel processing feature in R

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Who should go for this course?

The course is designed for all those who want to learn machine learning techniques with implementation in R language, and wish to apply these techniques on Big Data. The following professionals can go for this course:

1. Developers aspiring to be a ‘Data Scientist’
2. Analytics Managers who are leading a team of analysts
3. SAS/SPSS Professionals looking to gain understanding in Big Data Analytics
4. Business Analysts who want to understand Machine Learning (ML) Techniques
5. Information Architects who want to gain expertise in Predictive Analytics
6. ‘R’ professionals who want to captivate and analyze Big Data
7. Hadoop Professionals who want to learn R and ML techniques
8. Analysts wanting to understand Data Science methodologies

Please write back to us at or call us at +918880862004 or 18002759730 for more information.


Customer Reviews:

Gnana Sekhar Vangara, Technology Lead at, says, “Edureka Data science course provided me a very good mixture of theoretical and practical training. The training course helped me in all areas that I was previously unclear about, especially concepts like Machine learning and Mahout. The training was very informative and practical. LMS pre recorded sessions and assignmemts were very good as there is a lot of information in them that will help me in my job. The trainer was able to explain difficult to understand subjects in simple terms. Edureka is my teaching GURU now…Thanks EDUREKA and all the best. “

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8 Comments on "Linear Regression Algorithm | Linear Regression in R | Data Science Training | Edureka"

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Aymen Haj Kacem
Aymen Haj Kacem
13 days 19 hours ago

Please send the dataset to Thanks

Chinta Srinivasa Varma
Chinta Srinivasa Varma
14 days 5 hours ago

Super class, Could please share me the R code and Data set to srinuchinta@gmail.comThankyou

14 days 51 minutes ago

Hey Srinivasa, thanks for checking out our tutorial! We're glad you found it useful.We have shared the dataset with you. Do subscribe to our channel to stay posted on upcoming videos. Cheers!

maly Petu
maly Petu
30 days 5 hours ago

Hi There, congratulation on the excellent presentation. Could you please add the link to the Boston dataset.

25 days 19 hours ago

+maly Petu, thanks for checking out our tutorial. We're glad you found it useful.Please share your email address and we will send it. Cheers!

venkatesh gangireddy
venkatesh gangireddy
30 days 21 hours ago

Superb lecture .Could please share me the R code and Data set to –

25 days 19 hours ago

Hey Venkatesh, thanks for checking out our tutorial! We're glad you found it useful.We have shared it with you. Do subscribe to our channel to stay posted on upcoming videos. You can also check out our complete training here: Hope this helps. Cheers!

2 months 24 days ago

Very nice clearly explained