Keras is an open source neural network library that is written in the Python language. It should be noted that it is capable of running on top of other frameworks/software libraries, such as Microsoft Cognitive Toolkit, TensorFlow, and Theano. For those who don’t know, a neural network is actually a computing system that is meant to imitate the neural activity of animal brains, and is a collection of nodes called “artificial neurons”.

Keras as a neural network helps to optimize a lot of functions, and is used to make working with image and text data infinitely easier. This could help to improve productivity for countless platforms and companies who work with data. It is a tool that caters to the recent technological trend of deep learning, where companies are using AI to optimize their companies and find out more information about their consumer base, such as predictive trends or overall consumer trends.

Keras has over 200,000 users already, and was recently the 10th most cited tool in the 2018 Nuggets 2018 software poll, which indicates that it is rising in popularity and relevancy in the tech sector. It ultimately helps many companies experiment faster with certain processes, as well.

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    They are two model in this project; one is the original TP-GAN, and the other code was developed by me in order to improve the original result. know Both codes were tested on the same dataset MultiPLE dataset and model both result are good. The image quality result was good and loss accuracy loss including, generator loss, pixel loss, classify loss and most important is the identity preserving wa...

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    I'm an assistant professor at KAU and the work posted is related to my research. I need code to train a custom Deep Learning Model based on techniques proposed in the literature. Specifically, a custom LSTM as part of both the Neural Machine Translation (NMT) model seen here (https://colab.research.google.com/github/tensorflow/tensorflow/blob/r1.9/tensorflow/contrib/eager/python/examples/...

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    Deep Reinforcement Learning to find Decaying Sinusoids in Gaussian Noise

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    We are developing classifiers in TensorFlow 2.0 - these classifiers will analyse sequences of video frames of faces to ascertain certain behavioral characteristics e.g. yawning, smiling We require someone who is conversant in the application Deep Learning architectures (CNNs & RNNs) to Computer Vision problems and who is expert in Tensorflow 2.0. Not essential, but desirable, would be a knowle...

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