May 20, 2020

Transfer Learning in Convolutional Neural Networks simply explained

Transfer learning involves taking a pre-trained neural network and adapting the neural network to a new, different data set. Depending […]
January 30, 2020

Gated Recurrent Unit (GRU) With PyTorch

https://blog.floydhub.com/gru-with-pytorch/ Have you heard of GRUs? The Gated Recurrent Unit (GRU) is the younger sibling of the more popular Long Short-Term […]
January 30, 2020

Long Short-Term Memory Networks with PyTorch

LSTMs are a particular variant of RNNs, therefore having a grasp of the concepts surrounding RNNs will significantly aid your […]
January 28, 2020

Recurrent Neural Networks (RNN) with PyTorch

Recurrent Neural Networks(RNNs) have been the answer to most problems dealing with sequential data and Natural Language Processing(NLP) problems for […]
January 15, 2020

Object Detection using YOLO

Introduction How easy would our life be if we simply took an already designed framework, executed it, and got the […]
January 14, 2020

Fundamentals of Deep Learning

Introduction Did you know the first neural network was discovered in early 1950s ? Deep Learning (DL) and Neural Network […]
January 13, 2020

RCNN, fast RCNN, and faster RCNN algorithms for Object Detection Explained

Table of Contents A Simple Way of Solving an Object Detection Task (using Deep Learning) Understanding Region-Based Convolutional Neural Networks […]
January 11, 2020

Transfer Learning using PyTorch

Introduction to Transfer Learning Transfer Learning is a technique where a model trained for a certain task is used for […]