Generate faces by DCGANs
October 30, 2017
To understand how a machine can generate something it’s never seen before, you need to first understand what is Generative Adversarial Networks(GANs).
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To understand how a machine can generate something it’s never seen before, you need to first understand what is Generative Adversarial Networks(GANs).
Yesterday, Google released an amazing tool called AutoDraw . It recognises the strokes you draw and suggests well-drawn items by using Machine Learning. In this demo, we are going to use the same concept of Transfer Learning in the post (Style Transfer Network) from my previous post. Read more
This demo will show you how to build a neural network from scratch to carry out a prediction problem on a real dataset(UCI Machine Learning Database). Our goal here is to predict the number of bike share users on a given day.
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In this demo, I am gonna use a pre-trained model called vgg16(A CNN model) to implement a style transfer network to learn from a style image to an output image by using Transfer Learning. The training dataset of vgg used is called ImageNet.
