Building Recommender Systems with Machine Learning and AI free download

Frank Kane spent over nine years at Amazon, where he managed and led the development of many of Amazon’s personalized product recommendation systems . We’ll cover tried and true recommendation algorithms based on neighborhood-based collaborative filtering, and work up to more modern techniques including matrix factorization and deep learning with artificial neural networks . Along the way, you’ll learn from Frank’s extensive industry experience to understand the challenges you’ll encounter when applying these algorithms at large scale and with real-world data . Use Apache Spark to compute recommendations at large-scale on a cluster . Use K-Nearest-Neighbors to recommend items to users . Solve the “cold start” problem with content-based recommendations .Authentication failed. Unique API key is not valid for this user.

Who this course is for:

  • Software developers interested in applying machine learning and deep learning to product or content recommendations
  • Engineers working at, or interested in working at large e-commerce or web companies
  • Computer Scientists interested in the latest recommender system theory and research
File Name :Building Recommender Systems with Machine Learning and AI free download
Content Source:udemy
Genre / Category:Development
File Size :6.32 gb
Publisher :Sundog Education by Frank Kane
Updated and Published:05 May,2022

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