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Generative Adversarial Networks (GANs) belong to the family of generative models. They use the techniques of deep learning and neural network models. We can use GANs to generative many types of new data including images, texts, and even tabular data. In recent years, GANs have gained much popularity in the field of deep learning. And […] ...

Deep learning has picked up really well in recent years. Deep learning has had a positive and prominent impact in many fields. Computer vision, speech, NLP, and reinforcement learning are perhaps the most benefited fields among those. In this article, we will focus on how deep learning changed the computer vision field. We will get […] ...

Deep Learning neural networks can work well for several tasks today. We can use deep neural networks for image recognition, object detection, segmentation, speech, NLP and much more. But there is one problem with deep neural networks. They are bad at handling noise during real-world testing. The generalization power of deep neural networks reduces drastically […] ...