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Published on May 12, 2017 by Edureka

This Logistic Regression Tutorial shall give you a clear understanding as to how a Logistic Regression machine learning algorithm works in R. Towards the end, in our demo we will be predicting which patients have diabetes using Logistic Regression!

In this Logistic Regression Tutorial video you will understand:

1) The 5 Questions asked in Data Science
2) What is Regression?
3) Logistic Regression – What and Why?
4) How does Logistic Regression Work?
5) Demo in R: Diabetes Use Case
6) Logistic Regression: Use Cases

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#LogisticRegression #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 sales@edureka.co or call us at +918880862004 or 18002759730 for more information.

Website: www.edureka.co/data-science
Facebook: www.facebook.com/edurekaIN/
Twitter: twitter.com/edurekain
LinkedIn: www.linkedin.com/company/edureka

Customer Reviews:

Gnana Sekhar Vangara, Technology Lead at WellsFargo.com, 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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164 Comments on "Logistic Regression in R | Machine Learning Algorithms | Data Science Training | Edureka"

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bernard mathias
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bernard mathias
1 year 10 days ago

Thanks, guys!Would you like to provide a tutorial on building credit scorecard using R?.It will be of tremendous help

edureka!
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edureka!
1 year 3 days ago

Hey Bernard, thanks for checking out our tutorial.We have passed on your feedback to our team and we might come up with something on this topic in the future. Do subscribe to stay posted. Cheers!

bernard mathias
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bernard mathias
1 year 10 days ago

Thanks, guys!Would you like to provide a tutorial on building credit scorecard using R?.It will be of tremendous help

edureka!
Guest
edureka!
1 year 3 days ago

Hey Bernard, thanks for checking out our tutorial.We have passed on your feedback to our team and we might come up with something on this topic in the future. Do subscribe to stay posted. Cheers!

Deepesh Kataria
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Deepesh Kataria
1 year 1 month ago

HOW….IQ with 110 selected and IQ with 114 not selected….or it was just arbitrary ..!!!

edureka!
Guest
edureka!
1 year 1 month ago

Hey Deepesh, thanks for checking out our tutorial!It was added intentionally. As your model is never 100% accurate, it tries to find a correlation and hence segregates the result.Hope this helps. Cheers!

Deepesh Kataria
Guest
Deepesh Kataria
1 year 1 month ago

HOW….IQ with 110 selected and IQ with 114 not selected….or it was just arbitrary ..!!!

edureka!
Guest
edureka!
1 year 1 month ago

Hey Deepesh, thanks for checking out our tutorial!It was added intentionally. As your model is never 100% accurate, it tries to find a correlation and hence segregates the result.Hope this helps. Cheers!

Astrid Persson
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Astrid Persson
1 year 2 months ago
Really good video! I have used and interpreted logistic regression analyses before, without knowing how it works. It rises some questions though when comparing it to how I saw it then, as always when you "learn things the wrong way."When I used logistic regression I got odds ratios to compare tendencies of variables being more prevalent in one of two treatment groups or for each year's increase in age of a patient. To interpret significance, I used a confidence interval with 95% confidence level and of course the probability. How does this relate to what you have been explaining in… Read more »
edureka!
Guest
edureka!
1 year 1 month ago

Hey Astrid, thanks for checking out our tutorial! We're glad you found it useful.The confidence level is actually denoted by the asterisks ( * ) in the summary of the model. So, the number of asterisks actually determine the confidence level of that particular variable, and we try to incorporate those variables in the model, without losing the accuracy of the model. Hope this helps. Please feel free to get in touch with us if you have any more queries. Cheers!

Astrid Persson
Guest
Astrid Persson
1 year 2 months ago
Really good video! I have used and interpreted logistic regression analyses before, without knowing how it works. It rises some questions though when comparing it to how I saw it then, as always when you "learn things the wrong way."When I used logistic regression I got odds ratios to compare tendencies of variables being more prevalent in one of two treatment groups or for each year's increase in age of a patient. To interpret significance, I used a confidence interval with 95% confidence level and of course the probability. How does this relate to what you have been explaining in… Read more »
edureka!
Guest
edureka!
1 year 1 month ago

Hey Astrid, thanks for checking out our tutorial! We're glad you found it useful.The confidence level is actually denoted by the asterisks ( * ) in the summary of the model. So, the number of asterisks actually determine the confidence level of that particular variable, and we try to incorporate those variables in the model, without losing the accuracy of the model. Hope this helps. Please feel free to get in touch with us if you have any more queries. Cheers!

Suki Ramasamy
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Suki Ramasamy
1 year 2 months ago

good one

edureka!
Guest
edureka!
1 year 2 months ago

Hey Suki Ramasamy, thanks for checking out our tutorial! We're glad you found it useful. Here's another video that we thought you might like:

.Do subscribe to our channel to stay posted on upcoming tutorials. Cheers!

Suki Ramasamy
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Suki Ramasamy
1 year 2 months ago

good one

edureka!
Guest
edureka!
1 year 2 months ago

Hey Suki Ramasamy, thanks for checking out our tutorial! We're glad you found it useful. Here's another video that we thought you might like:

.Do subscribe to our channel to stay posted on upcoming tutorials. Cheers!

Chiranjeevi K
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Chiranjeevi K
1 year 2 months ago

Awesome.. My all doubts are cleared about the LR. Thanks for the video !!

edureka!
Guest
edureka!
1 year 2 months ago

Hey Chiranjeevi, thanks for checking out our tutorial! We're glad you found it useful. Here's another video that we thought you might like:

.Do subscribe to our channel to stay posted on upcoming tutorials. Cheers!

Chiranjeevi K
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Chiranjeevi K
1 year 2 months ago

Awesome.. My all doubts are cleared about the LR. Thanks for the video !!

edureka!
Guest
edureka!
1 year 2 months ago

Hey Chiranjeevi, thanks for checking out our tutorial! We're glad you found it useful. Here's another video that we thought you might like:

.Do subscribe to our channel to stay posted on upcoming tutorials. Cheers!

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