Linear Regression vs Logistic Regression Data Science Training Edureka

>> YOUR LINK HERE: ___ http://youtube.com/watch?v=OCwZyYH14uw

🔥 Data Science Certification using R (Use Code 𝐘𝐎𝐔𝐓𝐔𝐁𝐄𝟐𝟎 ): https://www.edureka.co/data-science-r... • This Edureka video on Linear Regression Vs Logistic Regression covers the basic concepts of linear and logistic models. The following topics are covered in this session: • (01:05) Types of Machine Learning • (03:09) Regression Vs Classification • (05:47) What is Linear Regression? • (09:22) What is Logistic Regression? • (13:26) Linear Regression Use Case • (15:02) Logistic Regression Use Case • (16:18) Linear Regression Vs Logistic Regression • Blog Series: http://bit.ly/data-science-blogs • Data Science Training Playlist: http://bit.ly/data-science-playlist • - - - - - - - - - - - - - - - - • Subscribe to our channel to get video updates. Hit the subscribe button above: https://goo.gl/6ohpTV • Instagram: / edureka_learning • Facebook: / edurekain • Twitter: / edurekain • LinkedIn: / edureka • - - - - - - - - - - - - - - - - • #linearregressionvslogisticregression #machinelearningalgorithms #linearregression #logisticregression #linearregressionalgorithm #logisticregressionalgorithm #machinelearning #datascience #datasciencetutorial #datasciencewithr #datasciencecourse #datascienceforbeginners #datasciencetraining #datasciencetutorial • - - - - - - - - - - - - - - - - • About the Course • Edureka's Data Science course will cover the whole data lifecycle ranging from Data Acquisition and Data Storage using R-Hadoop concepts, Applying modeling through R programming using Machine learning algorithms and illustrate impeccable Data Visualization by leveraging on 'R' capabilities. • - - - - - - - - - - - - - • 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. Analyze 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. Analyze 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 • • - - - - - - - - - - - - - • • 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. • • For online Data Science training, please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll-free) for more information.

#############################

New on site