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Tag Archives: Neural Network

Prerequisites: RNN The Hopfield Neural Networks, invented by Dr John J. Hopfield consists of one layer of ‘n’ fully connected recurrent neurons. It is generally… Read More
Contractive Autoencoder was proposed by the researchers at the University of Toronto in 2011 in the paper Contractive auto-encoders: Explicit invariance during feature extraction. The… Read More
Emotion Detection is one of the hottest topics in research nowadays. Emotion sensing technology can facilitate communication between machines and humans. It will also help… Read More
Neural Networks are a biologically-inspired programming paradigm that deep learning is built around. Python provides various libraries using which you can create and train neural… Read More
Hebbian Learning Rule, also known as Hebb Learning Rule, was proposed by Donald O Hebb. It is one of the first and also easiest learning… Read More
Prerequisite: ANN | Bidirectional Associative Memory (BAM) Learning AlgorithmTo implement BAM model, here are some essential consideration and approach-   Consider the value of M, as… Read More
DNN(Deep neural network) in a machine learning algorithm that is inspired by the way the human brain works. DNN is mainly used as a classification… Read More
GANs is an approach for generative modeling using deep learning methods such as CNN (Convolutional Neural Network). Generative modeling is an unsupervised learning approach that… Read More
Inception V4 was introduced in combination with Inception-ResNet by the researchers a Google in 2016. The main aim of the paper was to reduce the… Read More
Inception V1 (or GoogLeNet) was the state-of-the-art architecture at ILSRVRC 2014. It has produced the record lowest error at ImageNet classification dataset but there are… Read More
This article aims to implement a deep neural network with an arbitrary number of hidden layers each containing different numbers of neurons. We will be… Read More
The concept of Neural Networks is inspired by the neurons in the human brain and scientists wanted a machine to replicate the same process. This… Read More
Prerequisite: ANN | Self Organizing Neural Network (SONN) Learning Algorithm To implement a SONN, here are some essential consideration- Construct a Self Organizing Neural Network… Read More
Prerequisite: ANN | Self Organizing Neural Network (SONN) In the Self Organizing Neural Network (SONN), learning is performed by shifting the weights from inactive connections… Read More
Bidirectional Associative Memory (BAM) is a supervised learning model in Artificial Neural Network. This is hetero-associative memory, for an input pattern, it returns another pattern… Read More

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