PEMBELAJARAN MESIN UNTUK SISTEM REKOMENDASI
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Link Kuliah di Google Meet
RPS matakuliah
Buku Pegangan Kuliah
Slide Sistem Pemberi Rekomendasi [ATW]
01 Recommender Systems an Introduction
02 Recommender Systems' Inputs and Methods
03 Recommender Systems Evaluation
04 Collaboraitve Filtering I - Intuitive Methods
05 Collaborative Filtering II - Matrix Factorization
06 Collaborative Filtering III - More on Matrix Factorization
07 Content Based Filtering - Introductions
08 Content Based Filtering - TDFIDF
09 Knowledge Based RS
11 Hybrid Recommender Systems
12 Explaining Recommendations
13 Deep Learning Applications in Recommender Systems
15 Group Recommder Systems
Video Perkuliahan Pak Baizal
Video Pengantar Recommender System
Video 1 - Pengantar RecSys - Lanjutan
Video2 - Macam Input dalam RS
Video3 - Pengantar Collaborative Filtering - Intuitive Methods
Video User-Based Collaborative Filtering Part-2
Video Item-Based Collaborative Filtering - Part 1
Video Matrix Factorization
Video User-Based Collaborative Filtering Part-1
Video Content - Based filtering - Part 1
Video Evaluasi Performansi pada RecSys Part 2
Video Evaluasi Performansi pada RecSys
Video Knowledge Based Recommender System Part 1
Video pembahasan Kuis CLO1
Tugas dan Kuis [ATW]
Tugas 1 NDCG
Tugas CLO1 : user-based collaborative filtering
Tugas CLO3 : Implementasi User-Based CF
Kuis CLO 1
Tugas CLO2
Tugas Kelompok (CLO 2)
Tugas Besar (CLO3)
Tugas - Resume Materi
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CII7F3-31001
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CII7F3-31001
Summary
PEMBELAJARAN MESIN UNTUK SISTEM REKOMENDASI
Teacher:
Admin CELOE
Teacher:
Z. K. ABDURAHMAN BAIZAL
Teacher:
AGUNG TOTO WIBOWO