Building Recommendation Systems in Azure
Building Recommendation Systems in Azure
MP4 | Video: AVC 1280x720 | Audio: AAC 44KHz 2ch | Duration: 2.5 Hours | 3.60 GB
Genre: eLearning | Language: English
MP4 | Video: AVC 1280x720 | Audio: AAC 44KHz 2ch | Duration: 2.5 Hours | 3.60 GB
Genre: eLearning | Language: English
Machine Learning, or Data Science, is one of today's hottest buzzwords. The scenarios in which Azure Machine Learning can be applied are diverse and can range from predicting football scores to personalised recommendations in online shops to predictive maintenance in manufacturing. In this Microsoft Virtual Academy course I will go through various options on how to build recommendation systems using Microsoft Azure Machine Learning, and thus going beyond just finding the products in retail that are in high demand. We start off with an introduction module on machine learning and recommendation systems, followed by the simplest form of a machine learning problem – binary classification. Then we have a closer look at the two main ways to build a recommendation system using RStudio and AzureML. Finally, we go through a scenario using the Recommendations API provided in the Azure Marketplace.
Building Recommendation Systems in Azure
