Artificial Intelligence for IT/ITES by ISS National University of Singapore

Sessions, Workshop datasets and notebooks while training with National University of Singapore powered by LICT and Ministry of ICT, Bangladesh.

Resources:

Title	Domain	link
papers with code	Papers related to recommendation	link
Google Tutorials	Tutorials	link
Instacart market basket analysis	Market Basket Analysis	link github
Starspace Facebook	Recommendation	link
Food Discovery with Uber Eats: Recommending for the Marketplace	Recommendation	link
Food Discovery with Uber Eats: Building a Query Understanding Engine	Recommendation	link
Food Discovery with Uber Eats: Using Graph Learning to Power Recommendations	Recommendation	link
Implicit	Recommendation	link
Explicit	Recommendation	link
Meet Michelangelo: Uber’s Machine Learning Platform	Machine Learning Platform	link
Deepak Agarwal, Bee-Chung Chen, Pradheep Elango, and Xuanhui Wang. 2011. Click Shaping to Optimize Multiple Objectives. In KDD. ACM, New York, NY, USA, 132–140	Recommendation
Deepak Agarwal, Bee-Chung Chen, Pradheep Elango, and Xuanhui Wang. 2012. Personalized Click Shaping Through Lagrangian Duality for Online Recommendation. In SIGIR. ACM, New York, NY, USA, 485–494.	Recommendation
Meta-Graph: Few-Shot Link Prediction Using Meta-Learning	Meta learning	link
Evaluation Metrics for Recommender Systems	Evaluation	link
Popular evaluation metrics in recommender systems explained	Evaluation	link
Recommender Systems — It’s Not All About the Accuracy	Evaluation	link
Recommendation System Evaluation Metrics	Evaluation	link
Getting Started with a Movie Recommendation System	Kaggle	link
Film recommendation engine	Kaggle	link
Movie Recommender Systems Using Neural Network	Kaggle	link
Building_Recommender_System_with_Surprise	Github	link
Collaborative Filtering with Neural Networks	Github	link
Graph Convolutional Neural Networks for Web-Scale Recommender Systems	GCN Paper	link
Forecasting at Uber: An Introduction	Forecasting	link
Recommender Systems Handbook	Book	1 2
ACM RecSys	Conferences	link
Microsoft Research	Rec Github	link
List of Recommender Systems	Github	link
A Gentle Introduction to Recommender Systems with Implicit Feedback	Notebook	link
Matrix Factorization Surprise Implementation	Github	link
How Hulu Uses InfluxDB and Kafka to Scale to Over 1 Million Metrics a Second	Hulu Blog	link
Collaborative Filtering for Implicit Feedback Datasets	Paper	link
Datasets for recommendation systems	Datasets	link
Building Recommendation Engines with PySpark	Recommendation / Pyspark	link
Netflix Recommender System — A Big Data Case Study	Netflix recommendation	link
Build a Recommendation Engine With Collaborative Filtering	Collaborative filtering	link
Introducing TensorFlow Recommenders	Tensorflow Recommenders	link
Building a Recommendation System in TensorFlow: Overview	Google Cloud	link

Kaggle Notebooks:

Kernel Name	link
Food Recommendation Dataset Exploration	kernel
Recommender System	kernel
Recommendation engine exploration	kernel
Recommendation engine	kernel
Book Recommendations from Charles Darwin	kernel
Market Basket Analysis for Marketing Analytics	kernel

Secondary Resources

1. what-is-product-recommendation
2. product-recommendations
3. ecommerce-ai-recommender-system
4. product-recommendations
5. syte

Nvidia

1. Recommender Systems, Not Just Recommender Models