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    Machine Learning and Training Neural Network in MATLAB - Simpliv

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    Website https://www.simpliv.com/machinelearning/machine-learning-and-training-neural-network-in-matlab | Want to Edit it Edit Freely

    Category training;webinar

    Deadline: April 24, 2019 | Date: April 24, 2019-May 03, 2019

    Venue/Country: online course, U.S.A

    Updated: 2019-04-22 20:11:03 (GMT+9)

    Call For Papers - CFP

    About this Course

    Machine Learning is the up and upcoming branch of Artificial Intelligence and it holds great promises for the generations to come. In this course, we will talk about Machine Learning and Artificial Neural Networks and how you can implement a simple Machine Learning Model in MATLAB.

    Who this course is for:

    Anyone who is interested in learning basic concepts of Machine Learning and Neural networks

    Basic knowledge

    The course is beginner level for those who are interested in implementing Machine Learning in MATLAB. No prior technical Knowledge is required. However, if you are already familiar with MATLAB, it can be a plus point

    What you will learn

    You will learn about Machine Learning and how you can train a simple Model in MATLAB on a simple Dataset. You will get to know some basics of MATLAB too and how you can write and run scripts in MATLAB. You will be able to import your own dataset and train it using different parameters to make some interactive prediction model

    Contact Us:

    simplivllcatgmail.com

    Phone: 76760-08458

    Email: sudheeratsimpliv.com

    Phone: 9538055093

    To read more and register: https://www.simpliv.com/machinelearning/machine-learning-and-training-neural-network-in-matlab


    Keywords: Accepted papers list. Acceptance Rate. EI Compendex. Engineering Index. ISTP index. ISI index. Impact Factor.
    Disclaimer: ourGlocal is an open academical resource system, which anyone can edit or update. Usually, journal information updated by us, journal managers or others. So the information is old or wrong now. Specially, impact factor is changing every year. Even it was correct when updated, it may have been changed now. So please go to Thomson Reuters to confirm latest value about Journal impact factor.