RecSys

1.[boostcamp-ai-tech][RecSys] RecSys Basic(1) 추천시스템이란, 추천시스템의 평가 지표, 추천시스템 기법들(개요)

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2.[boostcamp-ai-tech][RecSys] RecSys Basic(2) 인기도 기반, 연관 분석, 콘텐츠 기반(TF-IDF)

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3.[boostcamp-ai-tech][RecSys] Collaborative Filtering(1) Neighborhood-based CF, Similarity Measure, Rating Prediction(CF)

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4.[boostcamp-ai-tech][RecSys] Collaborative Filtering(2) Model-Based CF: SVD, MF, BPR

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5.[boostcamp-ai-tech][RecSys] Item2Vec & ANN

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6.[boostcamp-ai-tech][RecSys] RecSys with DL(1) Neural Collaborative Filtering, YouTube Rec, RecSys with AutoEncoder, Multi-VAE

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7.[boostcamp-ai-tech][RecSys] RecSys with DL(2) Neural Graph Collaborative Filtering, LightGCN, GRU4Rec

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8.[boostcamp-ai-tech][RecSys] Context-aware Recommendation: FM, FFM, GBM, (Fuse Context with Latent Cross)

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9.[boostcamp-ai-tech][RecSys] DeepCTR: Wide&Deep, DeepFM, DIN, BST

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11.[boostcamp-ai-tech][RecSys] Markov Chains for Seq Rec, RNN for Seq Rec, Transformer-based Seq Rec, Rec with self-supervised learning

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12.Graph Neural Networks 쉽게 이해하기

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13.[RecSys] Embarrassingly Shallow Autoencoders for Sparse Data (2019)

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