Search results for "Generative Adversarial Networks"

In what order should I read your books?

A In what order should I read your books? What order should you read the books? That is a great question, my best suggestions are as follows: Consider starting with a book on a topic that you are most excited about. Consider starting with a book on a topic that you can apply on a […]

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Machine Learning Mastery Super Bundle

Machine Learning Mastery Super Bundle The Tools and Techniques That You Need To Get Really Good at Applied Machine Learning, Really Fast Save $449! That is 42.93% Off! If You’re Serious about Machine Learning… Then You Need This Bundle! Convinced? Check Out What Customers Are Saying… The Package You Need to Finally… Get Started and Get […]

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Machine Learning Mastery

EBooks

Frustrated with one-off articles and too much math? Take the Next Step and Get Tutorial-Based Playbooks that will Guide You to a Specific Result Welcome to: the Machine Learning Mastery EBook Catalog Popular | Beginner | Intermediate | Advanced | Bundles | Donate     Would you like to support Machine Learning Mastery? Consider a […]

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Machine Learning Mastery

Start Here with Machine Learning

Need Help Getting Started with Applied Machine Learning? These are the Step-by-Step Guides that You’ve Been Looking For! What do you want help with? The most common question I’m asked is: “how do I get started?” My best advice for getting started in machine learning is broken down into a 5-step process: Step 1: Adjust Mindset. […]

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Histogram of Two Different Probability Distributions for the Same Random Variable

How to Calculate the KL Divergence for Machine Learning

It is often desirable to quantify the difference between probability distributions for a given random variable. This occurs frequently in machine learning, when we may be interested in calculating the difference between an actual and observed probability distribution. This can be achieved using techniques from information theory, such as the Kullback-Leibler Divergence (KL divergence), or […]

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How to Implement Progressive Growing GAN Models in Keras

How to Implement Progressive Growing GAN Models in Keras

The progressive growing generative adversarial network is an approach for training a deep convolutional neural network model for generating synthetic images. It is an extension of the more traditional GAN architecture that involves incrementally growing the size of the generated image during training, starting with a very small image, such as a 4×4 pixels. This […]

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Plot of a Real Photo of a Horse, Translation to Zebra, and Reconstructed Photo of a Horse Using CycleGAN.

How to Develop a CycleGAN for Image-to-Image Translation with Keras

The Cycle Generative Adversarial Network, or CycleGAN, is an approach to training a deep convolutional neural network for image-to-image translation tasks. Unlike other GAN models for image translation, the CycleGAN does not require a dataset of paired images. For example, if we are interested in translating photographs of oranges to apples, we do not require […]

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Plot of Satellite to Google Map Translated Images Using Pix2Pix After 100 Training Epochs

How to Develop a Pix2Pix GAN for Image-to-Image Translation

The Pix2Pix Generative Adversarial Network, or GAN, is an approach to training a deep convolutional neural network for image-to-image translation tasks. The careful configuration of architecture as a type of image-conditional GAN allows for both the generation of large images compared to prior GAN models (e.g. such as 256×256 pixels) and the capability of performing […]

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How To Estimate The Performance of Machine Learning Algorithms in Weka

Deep Learning Courses

It can be difficult to get started in deep learning. Thankfully, a number of universities have opened up their deep learning course material for free, which can be a great jump-start when you are looking to better understand the foundations of deep learning. In this post you will discover the deep learning courses that you […]

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