Recommender

! My name is Kirill Khrylchenko, and I lead the RecSys R&D team at Yandex. One in all our goals is to develop transformer technologies inside the context of recommender systems, an objective we’ve...

Recommender systems are in every single place — whether you’re on Instagram, Netflix, or Amazon Prime. One common element among the many platforms is that all of them use recommender systems to tailor content...

A tour of crucial technological breakthroughs behind modern industrial recommender systemsAnd this concludes our tour. Allow me to summarize each of those landmarks with a single headline:: All we want are embeddings for users...

A tour of crucial technological breakthroughs behind modern industrial recommender systemsAnd this concludes our tour. Allow me to summarize each of those landmarks with a single headline:NCF: All we want are embeddings for users...

import surprisefrom surprise import Datasetfrom surprise import SVDfrom surprise.model_selection import train_test_splitfrom surprise import accuracy# Load the book-crossing datasetdata = Dataset.load_builtin('book-crossing')# Split the info into training and testing setstrainset, testset = train_test_split(data, test_size=0.2)# Define the...

Explanation of Recommendations through Matrix Factorization Maxwell Harper and Joseph A. Konstan. 2015. The MovieLens Datasets: History and Context. ACM Transactions on Interactive Intelligent Systems (TiiS) 5, 4: 19:1–19:19. https://doi.org/10.1145/2827872

Understanding probably the most underrated trick in applied Machine LearningHashing is some of the common “tricks” utilized in industrial Machine Learning applications, yet it doesn’t get nearly as much attention because it deserves.The largest...

Data science is one of the vital sought-after fields in today’s job market. With the ever-increasing amount of knowledge being generated each day, businesses are in need of expert data scientists who can extract...