inovex.deinovex.detwitterinstagramlinkedinxingyoutubefacebook
Avatar

Über Marcel Kurovski

Der Autor hat bisher keine Details angegeben.
Bisher hat Marcel Kurovski, 3 Blog Beiträge geschrieben.

RecSys 2020: Highlights of a Special Conference

2020-09-29T01:13:53+00:00

Read my take on the highlights of the 14th ACM Conference on Recommender Systems, such as the winners of the best long and short paper awards as well as an assortment of the best workshops and tutorials.

The 14th ACM Conference on Recommender Systems was special in many ways: a fully virtual conference that did an amazing job to keep social interaction alive – e

RecSys 2020: Highlights of a Special Conference2020-09-29T01:13:53+00:00

From Exploration to Production—Bridging the Deployment Gap for Deep Learning (Part 2)

2019-04-02T13:47:25+00:00

In this blogposts on deep learning model exploration, translation, and deployment we expand on the previous article with two additional approaches for model deployment: TensorFlow Serving and Docker as well as a rather hobbyist approach in which we build a simple web application that serves our model.

This is the second part of a series of two blogposts on deep learning model exploration, translation, and deployment. Both involve many technologies like PyTorch, Ten

From Exploration to Production—Bridging the Deployment Gap for Deep Learning (Part 2)2019-04-02T13:47:25+00:00

From Exploration to Production — Bridging the Deployment Gap for Deep Learning

2018-10-01T14:49:13+00:00

This article introduces EMNIST, we develop and train models with PyTorch, translate them with the Open Neural Network eXchange format ONNX and serve them through GraphPipe. We will orchestrate these technologies to solve the task of image classification using the more challenging and less popular EMNIST dataset.

This is the first part of a series of two blogposts on deep learning model exploration, translation, and deployment. Both involve many technologies like PyTorch, Tens

From Exploration to Production — Bridging the Deployment Gap for Deep Learning2018-10-01T14:49:13+00:00