gczh/applied-ml

Curated papers, articles, and blogs sharing how data science & machine learning is applied in production.

applied-ml

Curated papers, articles, and blogs sharing how data science & machine learning is applied in production. ⚙️

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Table of Contents

• Data Quality
• Data Engineering
• Classification
• Regression
• Recommendation
• Search/Ranking
• Natural Language Processing
• Sequence Modelling
• Computer Vision
• Reinforcement Learning
• Anomaly Detection
• Graph
• Optimization
• Information Extraction
• Validation and A/B Testing
• Practices

Data Quality

• Monitoring Data Quality at Scale with Statistical Modeling Uber
• An Approach to Data Quality for Netflix Personalization Systems Netflix

Data Engineering

• Zipline: Airbnb’s Machine Learning Data Management Platform Airbnb
• Sputnik: Airbnb’s Apache Spark Framework for Data Engineering Airbnb
• Feast: Bridging ML Models and Data Gojek

Classification

• High-precision phrase-based document classification on a modern scale LinkedIn
• Chimera: Large-Scale Classification using Machine Learning, Rules, and Crowdsourcing WalmartLabs
• Large-scale Item Categorization for e-Commerce DianPing, eBay
• Categorizing Products at Scale Shopify
• Learning to Diagnose with LSTM Recurrent Neural Networks Google
• Discovering and Classifying In-app Message Intent at Airbnb Airbnb
• How we built the good first issues feature GitHub

Regression

• Using Machine Learning to Predict Value of Homes On Airbnb Airbnb
• Modeling conversion rates and saving millions of dollars using Kaplan-Meier and gamma distributions Better
• Using machine learning to predict the value of ad requests Twitter

Recommendation

• Amazon.com Recommendations: Item-toItem Collaborative Filtering Amazon
• Recommending Complementary Products in E-Commerce Push Notifications with a Mixture Model Approach Alibaba
• Behavior Sequence Transformer for E-commerce Recommendation in Alibaba Alibaba
• Session-based Recommendations with Recurrent Neural Networks Telefonica
• Deep Neural Networks for YouTube Recommendations YouTube
• Personalized Recommendations for Experiences Using Deep Learning TripAdvisor
• E-commerce in Your Inbox: Product Recommendations at Scale Yahoo Product Recommendations at Scale](https://arxiv.org/abs/1606.07154) Yahoo
• Powered by AI: Instagram’s Explore recommender system Facebook
• Artwork Personalization at Netflix Netflix
• To Be Continued: Helping you find shows to continue watching on Netflix Netflix
• Learning a Personalized Homepage Netflix
• https://eng.uber.com/uber-eats-graph-learning/ Uber
• Calibrated Recommendations Netflix
• Explore, Exploit, and Explain: Personalizing Explainable Recommendations with Bandits Spotify
• For Your Ears Only: Personalizing Spotify Home with Machine Learning Spotify
• Reach for the Top: How Spotify Built Shortcuts in Just Six Months Spotify
• The Evolution of Kit: Automating Marketing Using Machine Learning Shopify
• Using machine learning to predict what file you need next (Part 1) Dropbox
• Using machine learning to predict what file you need next (Part 2) Dropbox
• A closer look at the AI behind course recommendations on LinkedIn Learning (Part 1) LinkedIn
• A closer look at the AI behind course recommendations on LinkedIn Learning (Part 2) LinkedIn
• A recommender system in 30 lines of Clojure Findka.com

Search/Ranking

• Amazon Search: The Joy of Ranking Products Amazon
• How Lazada Ranks Products to Improve Customer Experience and Conversion Lazada
• Using Deep Learning at Scale in Twitter’s Timelines Twitter
• Machine Learning-Powered Search Ranking of Airbnb Experiences Airbnb
• Applying Deep Learning To Airbnb Search Airbnb
• Ranking Relevance in Yahoo Search Yahoo
• An Ensemble-Based Approach to Click-Through Rate Prediction for Promoted Listings at Etsy Etsy
• Why Do People Buy Seemingly Irrelevant Items in Voice Product Search? Amazon
• The AI Behind LinkedIn Recruiter search and recommendation systems LinkedIn
• AI at Scale in Bing Microsoft
• Query Understanding Engine in Traveloka Universal Search Traveloka
• Search-based User Interest Modeling with Lifelong Sequential Behavior Data for Click-Through Rate Prediction Alibaba
• The Secret Sauce Behind Search Personalisation GoJek

Embeddings

• Billion-scale Commodity Embedding for E-commerce Recommendation in AlibabaAlibaba
• Embeddings@Twitter Twitter
• Listing Embeddings in Search Ranking (Paper) Airbnb

Natural Language Processing

• Abusive Language Detection in Online User Content Yahoo
• How natural language processing helps LinkedIn members get support easily LinkedIn
• Building Smart Replies for Member Messages LinkedIn
• Smart Reply: Automated Response Suggestion for Email Google
• Assistive AI Makes Replying Easier Microsoft
• AI advances to better detect hate speech Facebook
• Using Neural Networks to Find Answers in Tables Google
• A Scalable Approach to Reducing Gender Bias in Google Translate Google
• A state-of-the-art open source chatbot Facebook
• Goal-Oriented End-to-End Conversational Models with Profile Features in a Real-World Setting Amazon
• How Gojek Uses NLP to Name Pickup Locations at Scale GoJek

Sequence Modelling

• Recommending Complementary Products in E-Commerce Push Notifications with a Mixture Model Approach Alibaba
• Practice on Long Sequential User Behavior Modeling for Click-Through Rate Prediction Alibaba
• Learning to Diagnose with LSTM Recurrent Neural Networks Google
• Deep Learning for Understanding Consumer Histories Zalando
• Continual Prediction of Notification Attendance with Classical and Deep Network Approaches Telefonica

Computer Vision

• Categorizing Listing Photos at Airbnb Airbnb
• Amenity Detection and Beyond — New Frontiers of Computer Vision at Airbnb Airbnb
• Powered by AI: Advancing product understanding and building new shopping experiences Facebook
• Creating a Modern OCR Pipeline Using Computer Vision and Deep Learning Dropbox
• How we improved computer vision metrics by more than 5% only by cleaning labelling errors Deepomatic
• A Neural Weather Model for Eight-Hour Precipitation Forecasting Google
• Converting text to images for product discovery Amazon

Reinforcement Learning

• Deep Reinforcement Learning for Sponsored Search Real-time Bidding Alibaba
• Dynamic Pricing on E-commerce Platform with Deep Reinforcement Learning Alibaba
• Budget Constrained Bidding by Model-free Reinforcement Learning in Display Advertising Alibaba
• Productionizing Deep Reinforcement Learning with Spark and MLflow Zynga

Anomaly Detection

• Detecting Performance Anomalies in External Firmware Deployments Netflix
• Detecting and preventing abuse on LinkedIn using isolation forests LinkedIn
• Uncovering Insurance Fraud Conspiracy with Network Learning Ant Financial

Graph

• Retail Graph — Walmart’s Product Knowledge Graph Walmart

Optimization

• How Trip Inferences and Machine Learning Optimize Delivery Times on Uber Eats Uber

Information Extraction

• Unsupervised Extraction of Attributes and Their Values from Product Description Rakuten
• Information Extraction from Receipts with Graph Convolutional Networks Nanonets

Validation and A/B Testing

• The reusable holdout: Preserving validity in adaptive data analysis Google
• A/B Testing with Hierarchical Models in Python Domino
• Detecting interference: An A/B test of A/B tests LinkedIn
• Building inclusive products through A/B testing LinkedIn
• Experimenting to solve cramming Twitter
• Announcing a New Framework for Designing Optimal Experiments with Pyro Uber
• Enabling 10x More Experiments with Traveloka Experiment Platform Traveloka

Practices

• Practical Recommendations for Gradient-Based Training of Deep Architectures Yoshua Bengio
• Machine Learning: The High Interest Credit Card of Technical Debt Google
• Rules of Machine Learning: Best Practices for ML Engineering Google
• Hidden Technical Debt in Machine Learning Systems Google
• On Challenges in Machine Learning Model Management Amazon
• 150 successful Machine Learning models: 6 lessons learned at Booking.com Booking.com