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Learning to Rank with XGBoost and GPU

This article was originally published at NVIDIA’s website. It is reprinted here with the permission of NVIDIA. XGBoost is a widely used machine learning library, which uses gradient boosting techniques to incrementally build a better model during the training phase by combining multiple weak models. Weak models are generated by… Learning to Rank with XGBoost …

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The Guide to Machine Learning in Retail: Applications and Use Cases

This article was originally published at Tryolabs’ website. It is reprinted here with the permission of Tryolabs. Introduction Artificial intelligence (AI) and machine learning (ML) are among the top technology trends in the retail world. They are having a great impact on the industry, in particular in e-commerce companies that… The Guide to Machine Learning …

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Building a Real-time Redaction App Using NVIDIA DeepStream, Part 2: Deployment

This article was originally published at NVIDIA’s website. It is reprinted here with the permission of NVIDIA. This post is the second in a series (Part 1) that addresses the challenges of training an accurate deep learning model using a large public dataset and deploying the model on the edge… Building a Real-time Redaction App …

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Building a Real-time Redaction App Using NVIDIA DeepStream, Part 1: Training

This article was originally published at NVIDIA’s website. It is reprinted here with the permission of NVIDIA. Some of the biggest challenges in deploying an AI-based application are the accuracy of the model and being able to extract insights in real time. There’s a trade-off between accuracy and inference throughput. Making the model more accurate …

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A Guide to Video Analytics: Applications and Opportunities

This article was originally published at Tryolabs’ website. It is reprinted here with the permission of Tryolabs. Introduction In the past few years, video analytics, also known as video content analysis or intelligent video analytics, has attracted increasing interest from both industry and the academic world. Thanks to the enormous advances made in deep learning, …

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Machine Learning On Edge Devices: Benchmark Report

This article was originally published at Tryolabs’ website. It is reprinted here with the permission of Tryolabs. Why edge computing? Humans are generating and collecting more data than ever. We have devices in our pockets that facilitate the creation of huge amounts of data, such as photos, gps coordinates, audio, and all kinds of personal …

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Cloud and Edge Vision Processing Options for Deep Learning Inference

Should deep learning-based computer vision processing take place in the cloud, at the edge, or both? This seemingly simple question has a complicated answer: "it depends." This article provides perspectives on the various factors you should consider, and with what priorities, when making this implementation decision for your particular project's requirements. THe Edge-Centric Inference Evolution …

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Rapid Prototyping on NVIDIA Jetson Platforms with MATLAB

This article was originally published at NVIDIA’s website. It is reprinted here with the permission of NVIDIA. This article discusses how an application developer can prototype and deploy deep learning algorithms on hardware like the NVIDIA Jetson Nano Developer Kit with MATLAB. In previous posts, we explored how you can design and train deep learning …

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