May 20, 2020
Published by Amir Masoud Sefidian at May 20, 2020
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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 […]
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January 30, 2020
Published by Amir Masoud Sefidian at January 30, 2020
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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 […]
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January 30, 2020
Published by Amir Masoud Sefidian at January 30, 2020
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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 […]
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January 28, 2020
Published by Amir Masoud Sefidian at January 28, 2020
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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 […]
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January 15, 2020
Published by Amir Masoud Sefidian at January 15, 2020
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Object Detection using YOLO

Introduction How easy would our life be if we simply took an already designed framework, executed it, and got the […]
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January 14, 2020
Published by Amir Masoud Sefidian at January 14, 2020
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Fundamentals of Deep Learning

Introduction Did you know the first neural network was discovered in early 1950s ? Deep Learning (DL) and Neural Network […]
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January 13, 2020
Published by Amir Masoud Sefidian at January 13, 2020
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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 […]
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January 11, 2020
Published by Amir Masoud Sefidian at January 11, 2020
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Transfer Learning using PyTorch

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