PerceptiLabs Blog

Using ResNets to Detect Anomalies in Industrial IoT Textile Production

Oct 8, 2020 3:08:16 PM / by PerceptiLabs posted in Machine Learning, MLOps, Model building, datasets, ResNet, residual block

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Machine learning models for image classification often use convolutional neural networks (CNNs) to extract features from images while employing max-pooling layers to reduce dimensionality. The goal is to extract increasingly higher-level features from regions of the image, to ultimately make some kind of prediction such as an image classification.

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Announcing PerceptiLabs' October 2020 Silver 0.11 Release

Oct 6, 2020 7:24:12 AM / by PerceptiLabs posted in Machine Learning, MLOps, Model building, datasets, visual modeling tool, TensorFlow, AutoML

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PerceptiLabs is proud to announce the first major Silver release of our visual machine learning (ML) modeling tool, PerceptiLabs 0.11. Not only does this release candidate include a number of significant new features, functionality, and UI improvements, it also offers more stability than our past beta versions. Through these enhancements, PerceptiLabs is becoming the GUI for TensorFlow–you drag and drop the components, and PerceptiLabs generates the visualizations and TensorFlow code for you. 

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PerceptiLabs Releases Free Source Code for Our Machine Learning Handbook

May 20, 2020 1:16:57 PM / by PerceptiLabs posted in Machine Learning, Model Management, Model building, Modeling Tool

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Here at PerceptiLabs we love exploring all sorts of machine learning (ML) approaches. And if you've poked around our site in the last little while, you may have come across our Machine Learning Handbook. It's a free resource that you can download and use to become more familiar with approaches like linear regression, decision trees, k-nearest neighbor, support vector machines (SVMs), clustering, and of course, neural networks.

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Four Common Types of Neural Network Layers (and When to use Them)

May 20, 2020 1:04:11 PM / by PerceptiLabs posted in Machine Learning, Model Management, MLOps, Explainability, Model building, Modeling Tool, Hyperparameters

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Neural networks (NN) are the backbone of many of today's machine learning (ML) models, loosely mimicking the neurons of the human brain to recognize patterns from input data. As a result, numerous types of neural network topologies have been designed over the years, built using different types of neural network layers.

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Drag and Drop your way to a new Machine Learning Model

Dec 20, 2019 9:00:00 AM / by PerceptiLabs posted in Transparency, Flexibility, Machine Learning, Model building, Modeling Tool

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Introducing PerceptiLabs, a Visual Modeling Tool for Machine Learning

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