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    100% Discount || Logistic Regression in R Studio

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    Logistic Regression in R Studio

    Requirements

    • Students will need to install R and R studio software but we have a separate lecture to help you install the same

    Description

    You’re looking for a complete Classification modeling course that teaches you everything you need to create a Classification model in R, right?

    You’ve found the right Classification modeling course covering logistic regression, LDA and kNN in R studio!

    After completing this course, you will be able to:

    · Identify the business problem which can be solved using Classification modeling techniques of Machine Learning.

    · Create different Classification modelling model in R and compare their performance.

    · Confidently practice, discuss and understand Machine Learning concepts

    How this course will help you?

    Verifiable Certificate of Completion is presented to all students who undertake this Machine learning basics course.

    If you are a business manager or an executive, or a student who wants to learn and apply machine learning in Real world problems of business, this course will give you a solid base for that by teaching you the most popular Classification techniques of machine learning, such as Logistic Regression, Linear Discriminant Analysis and KNN

    Why should you choose this course?

    This course covers all the steps that one should take while solving a business problem using classification techniques.

    Most courses only focus on teaching how to run the analysis but we believe that what happens before and after running analysis is even more important i.e. before running analysis it is very important that you have the right data and do some pre-processing on it. And after running analysis, you should be able to judge how good your model is and interpret the results to actually be able to help your business.

     

    Who this course is for:

    • People pursuing a career in data science
    • Working Professionals beginning their Data journey
    • Statisticians needing more practical experience


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