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Showing posts from October 13, 2020

Jobs lost During Covid-19

  Nowadays, Lots of persons lost his/her job during pandemic situations. We should prepare for this type of disasters in our life. Also the government has not provided any facility to these types of persons who lost his/her job. Due to private employee no any systems have formed by our government to protect, so we need to raise our voice about these things. Our government should interfere in between these types of decision which is taken by private employers. Also, some private employers have got less salary during pandemic situations and after that not considered completed salary. During these days, also the government is facing lots of problems and lots of civilians have died in the hospital as well as in the quarantine center due to this covid-19. In all over the world lots of persons have died due to no any medicine of covid-19. Our government should make a facility to counter such type of disasters in the future. We can see in the social media and with the communication of our...

Generative Adversarial Networks (GAN’s)

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  Generative Adversarial Networks (GAN’s), or GAN depend on Generative demonstrating and utilize solo learning in AI which includes understanding examples in the accessible information or pictures in the way where we train the information and expect some next examples situated in generative models. This is actually quite helpful when we are working with unsupervised learning models.          Figure 1: Generative Model Generative Adversarial Networks (GAN's) are unsupervised learning based models which utilizes two neural networks contend with one other to produce various examples of information. Generative Adversarial Networks (GAN's) models utilizes generative functions and discriminator functions. generator function stage that utilizes a few examples and produces new example of same information. Discriminator networks fundamentally done characterization and attempt to coordinate this example with accessible preparing information and attemp...