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Udemy - Machine Learning Made Easy : Beginner to Advanced using R

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????For More Udemy Courses Visit  ???????? Course Drive
 



Machine Learning Made Easy : Beginner to Advanced using R
 

Learn Machine Learning Algorithms using R from experts with hands on examples and practice
sessions. With 5 different pr 
 


 


What you'll learn  

•	R Programming, Data Handling and Cleaning, Basic Statistics,
Classical Machine Learning Algorithms, Model Selection and Validation, Advanced Machine Learning Algorithms, Ensemble
Learning. 
•	Write your own R scripts and work in R environment. 
•	Import, manipulate, clean up, sanitize
and export datasets. 
•	Understand basic statistics and implement using R. 
•	Understand data science life
cycle while understanding steps of building, validating, improving and implementing the machine learning models. 
•	Do powerful analysis on data, find insights and present them in visual manner. 
•	Learn classical
algorithms like Linear Regression, Logistic Regression, Decision Trees and advance machine learning algorithms like SVM,
Artificial Neural Networks, Reinforced Learning, Random Forests and Boosting and clustering algorithms like K-means. 
•	Know how each machine learning algorithm works and which one to choose according to the type of problem. 
•	Build more than one powerful machine learning model and be able to select the best one and improve it further. 

Requirements  

•	Familiarity with high school mathematics. 


Description  

Want to know how Machine Learning algorithms work and how people apply it to
solve data science problems? You are looking at right course! 
This course has been created, designed and assembled
by professional Data Scientists who have worked in this field for nearly a decade. We can help you understand the
complex machine learning algorithms while keeping you grounded to the implementation on real business and data science
problems. 
We will let you feel the water and coach you to become a full swimmer in the realm of data science and
Machine Learning. Every tutorial will increase your skill level by challenging your ability to foresee, yet letting you
improve upon self. 
We are sure that you will have fun while learning from our tried and tested structure of course
to keep you interested in what’s coming next. 
Here is how the course is going to work: 
•	Part 1 –
Introduction to R Programming. 
o	This is the part where you will learn basic of R programming and familiarize
yourself with R environment. 
o	Be able to import, export, explore, clean and prepare the data for advance
modeling. 
o	Understand the underlying statistics of data and how to report/document the insights. 
•	Part 2
– Machine Learning using R 
o	Learn, upgrade and become expert on classic machine learning algorithms like Linear
Regression, Logistic Regression and Decision Trees. 
o	Learn which algorithm to choose for specific problem, build
multiple model, learn how to choose the best model and be able to improve upon it. 
o	Move on to advance machine
learning algorithms like SVM, Artificial Neural Networks, Reinforced Learning, Random Forests and Boosting and
clustering algorithms like K-means. 
Features: 
•	Fully packed with LAB Sessions. One to learn from and one
for you to do it yourself. 
•	Course includes R code, Datasets and other supporting material at the beginning of
each section for you to download and use on your own. 
•	Quiz after each section to test your learning. 


Bonus: 
•	This course is packed with 5 projects on real data related to different domains to prepare you
for wide variety of business problems. 
•	These projects will serve as your step by step guide to solve different
business and data science problems. 
 

Who this course is for:  

•	Anyone
interested in Data Science and Machine Learning. 
•	Students who want a head start in Data Science field. 
•	Data analysts who want to upgrade their skills in Machine Learning. 
•	People who want to add value to
their work and business by using Machine Learning. 
•	People with basics understanding of classical machine
learning algorithms like linear regression or logistic regression, but want to learn more about it. 
•	People
interested in understanding application of machine learning algorithms on real business problems. 
•	People
interested in understanding how a machine learning algorithm works and what's the math behind it. 



 
 

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