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    Artificial Intelligence II – Neural Networks in Java

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    Artificial Intelligence II - Neural Networks in Java - Online Course Download
    Artificial Intelligence II - Neural Networks in Java - Online Course Download
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    Artificial Intelligence Data Science Development free online course free udemy paid course freecourse freecoursesite udemy course download udemy courses free download

    What you'll learn :

    Basics of neural networks
    Hopfield networks
    Concrete implementation of neural networks
    Backpropagation
    Optical character recognition

     

    Requirements :

    Basic Java

    Description :

    This course is about artificial neural networks. Artificial intelligence and machine learning are getting more and more popular nowadays. In the beginning, other techniques such as Support Vector Machines outperformed neural networks, but in the 21th century neural networks again gain popularity. In spite of the slow training procedure, neural networks can be very powerful. Applications ranges from regression problems to optical character recognition and face detection.

    Section 1:

    what are neural networks

    modeling the human brain

    the big picture

    Section 2:

    Hopfield neural networks

    Section 3:

    what is back-propagation

    feedforward neural networks

    optimizing the cost function

    error calculation

    backpropagation and resilient propagation

    Section 4:

    the single perceptron model

    solving linear classification problems

    logical operators (AND and XOR operation)

    Section 5:

    applications of neural networks

    clustering

    classification (Iris-dataset)

    optical character recognition (OCR)

    In the first part of the course you will learn about the theoretical background of neural networks, later you will learn how to implement them.

    If you are keen on learning methods, let’s get started!

    Who this course is for :

    This course is recommended for students who are interested in artificial intelligence focusing on neural networks

    Course Size Details :

    5 hours on-demand video
    1 article
    1 downloadable resource
    Full lifetime access
    Access on mobile and TV
    Certificate of completion

    View Demo

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