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    100% Discount || Machine Learning & Deep Learning in Python & R

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    Machine Learning & Deep Learning in Python & R

    Requirements
    Students will need to install Anaconda software but we have a separate lecture to guide you install the same
    Description
    You’re looking for a complete Machine Learning and Deep Learning course that can help you launch a flourishing career in the field of Data Science & Machine Learning, right?

    You’ve found the right Machine Learning course!

    After completing this course you will be able to:

    · Confidently build predictive Machine Learning and Deep Learning models to solve business problems and create business strategy

    · Answer Machine Learning related interview questions

    · Participate and perform in online Data Analytics competitions such as Kaggle competitions

    Check out the table of contents below to see what all Machine Learning and Deep Learning models you are going to learn.

    How this course will help you?

    A 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 techniques of machine learning.

    Why should you choose this course?

    This course covers all the steps that one should take while solving a business problem through linear regression.

    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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