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Deep Learning – Introduction to Generative Adversarial Neural Networks (GANs)

Generative Adversarial Networks (GANs) – A very young family member of Deep Neural Networks Architecture. Introduce by Ian Goodfellow and his team at the University of Montreal in 2014. GANs are class of unsupervised machine learning algorithm.  Adversarial training “The most interesting idea in the last 10 years in the field of Machine Learning.”           …

Deep Learning – Introduction to Recurrent Neural Networks

Recurrent Neural Networks – Main use of RNNs are when using google or facebook these interfaces are able to predict next word what you are about to type. RNNs have loops to allow information to persist. RNN’s are considered to be fairly good for modeling sequence data. Recurrent neural networks are linear architectural variant of recursive networks.…

Deep Learning – Introduction to Convolutional Neural Networks

Convolutional Neural Network – In this article, we will explore our intuitive explanation of convolutional neural networks (CNN’s) on high level. CNN’s are inspired by the structure of the brain but our focus will not be on neural science in here as we do not specialise in any biological aspect. We are going artificial in this…

Deep Learning – Introduction to Basics

Deep Learning (DL) – A very young and limitless field. Its a class of machine learning where theories of the subject aren’t strongly established and views quickly changes almost on daily basis. “I think people needs to understand that deep learning is making a lot of things, behind the scenes, much-better” – Sir Geoffrey Hinton What is Deep…