TowardsMachineLearning

Deep Learning

Introduction to GANs: Adversarial attacks and Defenses for Deep Learning

Introduction to GANs: Adversarial attacks and Defenses for Deep Learning The popularity of deep learning is growing, we are using the neural nets in every field to increase the productivity and the capabilities and of course neural nets has a lot of potential which can easily be justified by seeing their application. So till time, …

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Convolutional Neural Networks

Convolutional Neural Networks Brief introduction- Convolutional Neural networks also known as ConvNets or CNN. ConvNet is famous for image analysis and classification tasks and so are frequently used in machine learning applications targeted at medical images. They also have an excellent capacity in sequent data analysis such as NLP(Natural Language Processing). Some of the application …

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RCNN Simplified

RCNN Simplified (Region Based Convolutional Neural Network) Why need RCNN when we have a sliding window ?? Before using RCNN the approach to do object detection was through the sliding window concept, which of course was very computationally expensive and time consuming to slide through the whole image and that too with windows of different …

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Recurrent Neural Network (RNN) architecture explained in detail

Introduction:- In this article I would assume that you have a basic understanding of neural networks . In this article,we’ll talk about Recurrent Neural Networks aka RNNs that made a major breakthrough in predictive analytics for sequential data. This article we’ll cover the architecture of RNNs ,what is RNN , what was the need of …

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