Convolutional Neural Networks: Zero to Full Real-World Apps

The BEST Resource for Creating your own Convolutional Neural Networks Applications

Convolutional Neural Networks: Zero to Full Real-World Apps
Convolutional Neural Networks: Zero to Full Real-World Apps
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).

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

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  • 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)

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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

Convolutional Neural Networks: Zero to Full Real-World Apps udemy courses free download

The BEST Resource for Creating your own Convolutional Neural Networks Applications


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