Building Recommender Systems with Machine Learning and AI [Video]
English | Size: 2.92 GB
Category: CBTs
Frank Kane spent over nine years at Amazon, where he managed and led the development of many of Amazon’s personalized product recommendation technologies. You’ve seen automated recommendations everywhere-on Netflix’s home page, on YouTube, and on Amazon-as these machine learning algorithms learn about your unique interests, and show the best products or content for you as an individual. These technologies have become central to the largest, most prestigious tech employers out there, and by understanding how they work, you’ll become very valuable to them. We cover tried-and-true recommendation algorithms based on neighborhood-based collaborative filtering and work our way up to more modern techniques including matrix factorization and even deep learning with artificial neural networks.
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