1. Introduction
  2. Current Focus
  3. Recommender Systems
    1. Recent Trends
    2. Gradient Boosting
    3. TF-IDF
    4. Cross Encoders
    5. SentenceTransformers
    6. Collaborative Filtering
    7. Evaluation
  5. AB Testing
    1. Examples
    2. Power Analysis
  7. LLMs
    1. Auto Prompt Optimization
    2. Fine-tuning
    3. Useful Models
    4. Encoder vs Decoder
    5. Contextualized Recommendations
  9. Statistics
    1. Conformal Predictions
  11. Miscellaneous
    1. Bradley-Terry Model
    2. Setting up WSL
    3. To Read
    4. Packages
    5. Skills
    6. Hash Collisions
  13. Identities
    1. Sigmoid
    2. Statistics
  15. Papers
    1. Weinberger 2009 - Hashing for Multitask Learning
    2. Rendle 2009 - Bayesian Personalized Ranking
    3. Burges 2010 - RankNET to LambdaMART
    4. Schroff 2015 - FaceNET
    5. Covington 2016 - Deep NNs for Youtube Recs
    6. Schnabel 2016 - Recs as Treatments
    7. Bateni 2017 - Affinity Clustering
    8. Guo 2017 - DeepFM
    9. Hamilton 2017 - GraphSAGE
    10. Ma 2018 - Entire Space Multi-Task Model
    11. Kang 2018 - SASRec
    12. Reimers 2019 - Sentence-BERT
    13. Yi 2019 - LogQ Correction for In Batch Sampling
    14. Zhao 2019 - Recommending What to Watch Next
    15. Lee 2020 - Large Scale Video Representation Learning
    16. He 2020 - LightGCN
    17. Lewis 2020 - Retrieval Augmented Generation
    18. Gao 2021 - GradCache
    19. Gao 2021 - SimCSE
    20. Weng 2021 - Contrastive Representation Learning
    21. Li 2021 - TaoBao Embedding-Based Retrieval
    22. Zou 2021 - PLM Based Ranking in Baidu Search
    23. Dao 2022 - Flash Attention
    24. Wei 2022 - CoT Prompting in LLMs
    25. Honovich 2022 - Instruction Induction
    26. Huang 2022 - LLMs can Self Improve
    27. Tunstall 2022 - SetFit
    28. Wang 2022 - Self Consistency LLM
    29. Rafailov 2023 - Direct Preference Optimization
    30. Blecher 2023 - Nougat
    31. Dong 2023 - MINE Loss
    32. Liu 2023 - Meaning Representations from Trajectories
    33. Klenitskiy 2023 - BERT4Rec vs SASRec
    34. Singh 2023 - Semantic IDs for Recs
    35. Yang 2023 - OPRO
    36. Rajput 2023 - Generative Retrieval
    37. Borisyuk 2024 - GNN at LinkedIn
    38. Wang 2024 - LLM for Pinterest Search
    39. Solatorio 2024 - GISTEmbed
    40. Sanjabi 2025 - 360Brew
    41. Zhang 2025 - Qwen3 Embedding
  17. Talks
    1. Yan 2025 - LLM for Recsys
    2. Tandon 2025 - Gemini for YouTube
    3. Hameed 2025 - 360Brew
  19. NLP Course
  20. Database Course
    1. Lecture 1
    2. Lecture 2
    3. Lecture 3
  22. RL Course
    1. Introduction
    2. MDPs
    3. Dynamic Programming
    4. Model Free Prediction
    5. Model Free Control
    6. Value Function Approximation
    7. Policy Gradient