Exploring Graph Neural Networks

Data Scientists at CRED, Ravi Kumar and Samiran Roy explained the essence of using graph neural networks and how the emerging technology is being utilised by CRED. 

On-Device Speech Representation Using TensorFlow Lite

Representation learning is a machine learning (ML) method that trains a model to discover prominent features. It may apply to a wide range of downstream tasks– including Natural Language Processing (BERT and ALBERT) and picture analysis and classification (Inception layers and SimCLR). Last year, researchers developed a baseline for comparing speech representations and a new, […]

Guide to Feed-Forward Network using Pytorch with MNIST Dataset

Feed Forward Neural Network

Neural Networks are a series of algorithms that imitate the operations of a human brain to understand the relationships present in vast amounts of data. Each “neuron” present in a neural network can be defined as a mathematical function that collects and classifies information according to the specific architecture. The network, in general, comprises interconnected […]

Using GANs For High-Resolution Cosmology Simulations

The Big Bang theory posits our Universe is ever-expanding. Edward Hubble has confirmed the Expanding Universe hypothesis through analysis of galactic redshifts. Currently, our Universe is about 93 billion light-years in diameter. Recently, researchers from Carnegie Mellon University and the University of California have developed a way to create a complex simulated universe in under […]