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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    As the title said, I want to predict if, given a certain time instant, a request will happen. Hopefully, I would like to have this working for more levels, i.e. Softmax Classification instead of Sigmoid Classification. The main description can be found in this StackExchange Post actually: [se connecter pour voir l'URL] You can also find a previous version of it in this Jupyter Notebook: [se ...

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    i am looking for ml programmer with experienced in research of 3-5yrs of experience in both, published papers in reputed journals or ugc approved journals atleast 10,12 papers in ai,ml,dl domain must work on interesed project implement code work as soon as possible and help in research paper writing

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    Hi I have a numeric dataset (not images) for apply deep learning classification. Dataset has 3 class but these are imbalanced sizes. For example class 1:200 , class 2:3200 , class 3:190 labels. I'm trying to train it in Keras or Tensorflow for classification. At the result; All prediction are collected in Class 2: So i searched the problem in internet and i found that i must define an weigh...

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    Semi-supervised Learning. Semi-supervised learning is a long-standing and important problem in Machine Learning. One of the main goals of generative modeling is to discover useful representations that can be used in the downstream tasks such as semi-supervised learning. The second problem is that these models tend to use all their capacity to capture the low-level pixel statistics, and hence the g...

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