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[{"id":483,"title":"Self-taught through trial and error","votes":552,"type":"x","order":1,"pct":78.63,"resources":[]},{"id":484,"title":"Formal training or courses","votes":30,"type":"x","order":2,"pct":4.27,"resources":[]},{"id":485,"title":"A job that required it","votes":34,"type":"x","order":3,"pct":4.84,"resources":[]},{"id":486,"title":"Other","votes":86,"type":"x","order":4,"pct":12.25,"resources":[]}] ["#ff5b00","#4ac0f2","#b80028","#eef66c","#60bb22","#b96a9a","#62c2cc"] ["rgba(255,91,0,0.7)","rgba(74,192,242,0.7)","rgba(184,0,40,0.7)","rgba(238,246,108,0.7)","rgba(96,187,34,0.7)","rgba(185,106,154,0.7)","rgba(98,194,204,0.7)"] 350
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78

Exploring Netflix’s Open Source Model for Better Recommendations

In this AI based Science article, we explore How Netflix adopted an Open Source Model to improve their Entertainment Recommender Systems.. First, let us discuss in brief, what Machine Learning basically means. In simple terms, Machine Learning is a technique by which a computer can “learn” from data, without using a complex set of different rules. This approach is mainly based on training a model from datasets. The better the quality of the datasets, the better the accuracy of the Machine Learning Model. The link for this article located at LinuxToday is no longer available. . First, let us discuss in brief, what Machine Learning basically means. In simple terms, Machine Lear. based, science, article, explore, netflix, adopted, source, model, improve. . LinuxSecurity.com Team

Calendar 2 Apr 14, 2018 User Avatar LinuxSecurity.com Team Vendors/Products
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[{"id":483,"title":"Self-taught through trial and error","votes":552,"type":"x","order":1,"pct":78.63,"resources":[]},{"id":484,"title":"Formal training or courses","votes":30,"type":"x","order":2,"pct":4.27,"resources":[]},{"id":485,"title":"A job that required it","votes":34,"type":"x","order":3,"pct":4.84,"resources":[]},{"id":486,"title":"Other","votes":86,"type":"x","order":4,"pct":12.25,"resources":[]}] ["#ff5b00","#4ac0f2","#b80028","#eef66c","#60bb22","#b96a9a","#62c2cc"] ["rgba(255,91,0,0.7)","rgba(74,192,242,0.7)","rgba(184,0,40,0.7)","rgba(238,246,108,0.7)","rgba(96,187,34,0.7)","rgba(185,106,154,0.7)","rgba(98,194,204,0.7)"] 350
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