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    Convolutional Neural Networks: Zero to Full Real-World Apps

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    Convolutional Neural Networks: Zero to Full Real-World Apps - Online Course Download
    Convolutional Neural Networks: Zero to Full Real-World Apps - Online Course Download
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    Convolutional Neural Networks Data Science Development free online course free udemy paid course freecourse freecoursesite udemy course download udemy courses free download

    What you'll learn :

    Understand the Similarities and Differences between NN vs. CNN
    Understand CNN Concepts and Architectures
    Analyze Live and Interactive CNN Applications
    Create your first CNN Real-World Application
    Submit your CNN Final Assignment for Final Review
    Friendly plain-English and direct to point explanations

     

    Requirements :

    1. Python +3.0
    2. Keras +2.0
    3. Your own Images Set (for Final Assignment project)
    4. My NN course (Optional, but highly recommended)

    Description :

    Some Student Reviews:

    “5/5 stars to Mauricio!” (March 2018).

    “The implementation part is very good and up-too the mark. The explanation step by step process is very good.” (February 2018).

    “course done very well; everything is explained in detail; really satisfied !!!” (February 2018).

    “Difficult topics are simply illustrated and therefore easy to understand.” (January 2018).

    “So far the course is good, clearly Explanation.” (November 2017).

    ═════════════════════════════════════════════════════

    ***Read the Quick FAQ for the entire course lowdown!***

    ═════════════════════════════════════════════════════

    NEW: Final Assignment submission lecture! Send in your CNN app and I’ll review it!

    NEW: Trophy Awards for Key Section Achievements!

    BONUS: Artificial Neural Networks Summary (for your Review and refreshment)

    ═════════════════════════════════════════════════════

    Hi. 

    As always, thanks for showing interest in this course!

    What makes this course special:

    Convolutional Neural Networks (CNN): Concepts, Visual Examples and Presentations

    Step-by-Step CNN Creation and Training

    Create your CNN application using your own Images

    Plus, personalized feedback and help. 

    You ask, I answer directly!

     

    ✅ First:

    You’ll start with the Neural Networks Review:

    Quickly learn/refresh all about Neural Networks (NNs): Feed-Forward Passes, Gradient Descent and Backpropagation,

    Refresh your memory about how NNs learn from data,

    After this, you will be ready and set to tackle Convolutional Neural Networks.

     

    ✅ Second: 

    You’ll start your Convolutional Neural Networks endeavor by reviewing their history and motivation:

    Why are they so good at prediction?

    What makes them so special?

    What were the first attempts?

     

     

    ✅ Third:

    You’ll continue your Convolutional Neural Networks endeavor by going into all required concepts:

    How does Convolutional Neural Networks read images? 

    What’s a Convolution layer and how to interpret it?

    What are the main components of Convolutional Layers?

    Then, learn how all Neural Network concepts stack into Convolutional Layers, i.e. activations, losses,

     

    ✅ Forth:

    Before jumping into code, you’ll see some Convolutional Neural Networks action:

    You’ll see 2 Convolutional Neural Networks LIVE,

    See how they learn right in front of your eyes,

    You’ll do exactly the same thing in the next sections! So go for it!

     

     

    ✅ Fifth:

    You’ll code your first Convolutional Neural Networks application:

    Code using the famous MNIST dataset,

    Easily understand all learnt concepts applied in this section,

    Tweak parameters according to your criteria and get a feel about how Convolutional Neural Networks learn from images.

     

    ✅ Sixth:

    Now it’s time for you to code your own Convolutional Neural Networks app with your own images:

    We’ll use the hydrangea (Kaggle) image dataset competition,

    Learn how to “take” images from your PC for your Convolutional Neural Networks app,

    Modify the parameters for the best learning process.

     

    ✅ Seventh:

    Submit your own Convolutional Neural Networks app as the course’s Final Assignment:

    Get comments on how to make it better

    Learn 100% by applying all concepts in this assignment

    Optimize for best results

     

    Lastly, you can post questions or doubts, and I’ll answer to you personally. 

     

    I’ll see you inside,

     

    -M.A. Mauricio M.

     

    Who this course is for :

    Professionals and/or Enthusiasts that need to create a CNN Real-World Application

    Course Size Details :

    View Demo

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