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Monitoring A Convolutional Neural Network (CNN) in Comet

Heartbeat

Tracking your image classification experiments with Comet ML Photo from nmedia on Shutterstock.com Introduction Image classification is a task that involves training a neural network to recognize and classify items in images. Before being fed into the network, the photos are pre-processed and shrunk to the same size.

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Introduction to Graph Neural Networks

Heartbeat

Neural networks leverage the structure and properties of graph and work in a similar fashion. Graph Neural Networks are a class of artificial neural networks that can be represented as graphs. Edge-level tasks , on the other hand, entail edge classification and link prediction.

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Train and host a computer vision model for tampering detection on Amazon SageMaker: Part 2

AWS Machine Learning Blog

Configure the CNN model In this step, we construct a minimal version of the VGG network with small convolutional filters. The VGG-16 consists of 13 convolutional layers and three fully connected layers. The following screenshot illustrates the architecture of our Convolutional Neural Network (CNN) model.

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How to Create Synthetic Data to Train Deep Learning Algorithms?

Dlabs.ai

In deep learning, a computer algorithm uses images, text, or sound to learn to perform a set of classification tasks. However, computer algorithms require a vast set of labeled data to learn any task – which begs the question: What can you do if you cannot use real information to train your algorithm? The answer?

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Big Medical Image Preprocessing With Apache Beam | A Step-by-Step Guide

Dlabs.ai

Kaggle is an online community for data scientists that regularly organizes data science contests. The Mayo Clinic sponsored the Mayo Clinic – STRIP AI competition focused on image classification of stroke blood clot origin. The solutions are then ranked, and the top competitors receive a prize.