Dishant Parikh - OpenGenus IQ: Learn Algorithms, DL, System Design

Disadvantages of RNN

We have explored the disadvantages of RNN in depth. Recurrent Neural Networks (or RNNs) are the first of their kind neural networks that can help in analyzing and learning sequences of data rather than just instance-based learning.

Machine Learning (ML)

Alternatives to CNN (Convolutional Neural Network)

We have explored Alternatives to CNN (Convolutional Neural Network) which includes Graph Neural Network and Capsule Neural Network.

Machine Learning (ML)

Variants of Graph Neural Networks (GNN)

In this article, we have explore the different types of Graph Neural Networks (GNN) which is classified based on graph type, propagation step and training method.

Machine Learning (ML)

Gated Graph Sequence Neural Networks (GGSNN)

Gated Graph Sequence Neural Networks (GGSNN) is a modification to Gated Graph Neural Networks which three major changes involving backpropagation, unrolling recurrence and the propagation model. We have explored the idea in depth.

Machine Learning (ML)

Overview of Graph Neural Networks

Graph neural network is a special kind of network, which works with a graph as a data sample. The typical neural network works with arrays, while GNN works with graphs.

Machine Learning (ML)

Edge Detection using Laplacian Filter

Laplacian Filter (also known as Laplacian over Gaussian Filter (LoG)), in Machine Learning, is a convolution filter used in the convolution layer to detect edges in input.

Machine Learning (ML)

Applications of Support Vector Machines (SVM)

Support Vector Machine (SVM) is a important ML model with several applications like Image-based analysis and classification tasks, Geo-spatial data-based applications, Text-based applications, Computational biology, Security-based applications and Chaotic systems control.