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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    Hello, I want you to do examples of Algorithms in Keras and give descriptive comments. For example: Notebook1: Do CNN example in keras and explanatory comments -> get paid 2.5$ Notebook2: Do RNN example in keras and expalanatory comments -> get paid 2.5$ I have a lot of requirement Notebook like this. So you may earn 100-150$. Don't bid without reading.

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    Face Recognition -- 7 5 dias left

    Project scope: They are two model. In this project; one is the original code which was downloaded from: [fazer login para ver a URL] , and the other code was developed by me in order to improve the original result. so, know Both codes were tested on the same dataset Multiple dataset and both result are good. The image quality result was good and loss accuracy loss including, generator loss, pixel...

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    I need you to design a time series prediction model (ARIMA) we will provide air quality data from 2015-2019. Design the model with that dataset and predict air quality parameters for 2020 then compare it with the 2020 actual data

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    Artigos da Comunidade dos Principais Keras