This is the last article in this series. This article is about another pre-trained CNN known as the ResNet along with an output visualization parameter known as the confusion matrix. ResNet This is also known as a residual network. It has three variations 51,101,151. They used a simple technique to […]
I am computational neuroscience and deep learning aspirant.
Currently, a student pursuing biomedical engineering at Rajalakshmi engineering college.
Looking on building a career in computational neuroscience.
I am an amateur in computer vision and trying to create innovative and different projects using computer vision.
writing has always been my passion from answer papers in school to the research papers in college and so on, there are a lot. I like to write in any format. I feel happy when I create awareness through my blogs.
I have started a book series on amazon named "inflammatory diseases" planning to publish 4 books in it.
I write articles under these domains namely food is medicine, disease explanation, human anatomy, deep learning, and so on.
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This article is about one of the pre-trained CNN models known as the VGG-16. The process of using a pretrained CNN is known as transfer learning. In this case, we need not build a CNN instead we can use this with a modification. The modifications are:- Removing the top (input) […]
The previous article was about the padding, stride, and parameters of CNN. This article is about the pooling and the procedure to build an image classifier. Pooling This is another aspect of CNN. There are different types of pooling like min pooling, max pooling, avg pooling, etc. the process is […]
The previous article was about the process of convolution and its implementation. This article is about the padding, stride and the parameters involved in a CNN. We have seen that there is a reduction of dimension in the output vector. A technique known as padding is done to preserve the […]
The previous article was about the procedure to develop a deep learning network and introduction to CNN. This article concentrates on the process of convolution which is the process of taking in two images and doing a transformation to produce an output image. This process is common in mathematics and […]
The previous article was on algorithm and hyper-parameter tuning. This article is about the general steps for building a deep learning model and also the steps to improve its accuracy along with the second type of network known as CNN. General procedure to build an AI machine Obtain the data […]
The previous article dealt with the networks and the backpropagation algorithm. This article is about the mathematical implementation of the algorithm in FFN followed by an important concept called hyper-parameter tuning. In this FFN we apply the backpropagation to find the partial derivative of the loss function with respect to […]
The previous article gave some introduction to the networks used in deep learning. This article provides more information on the different types of neural networks. In a feed-forward neural network (FFN) all the neurons in one layer are connected to the next layer. The advantage is that all the information […]
The previous article gave a brief introduction to deep learning. This article deals with the networks used in deep learning. This network is known as a neural network. As the name suggests the network is made up of neurons The networks used in artificial intelligence are a combination of blocks […]
Have you ever wondered how the brain works? One way of understanding it is by cutting open the brain and analyzing the structures present inside it. This however can be done by researchers and doctors. Another method is by using electricity to stimulate several regions of the brain. But what […]