Tag:
teardown
(10)
SearchContent Moderation & Fraud Detection - Patterns in Industry
Collecting ground truth, data augmentation, cascading heuristics and models, and more.
26 Feb 2023 · 16 min · teardown machinelearning production
Bandits for Recommender Systems
Industry examples, exploration strategies, warm-starting, off-policy evaluation, and more.
08 May 2022 · 14 min · teardown recsys machinelearning
Reinforcement Learning for Recommendations and Search
Focusing on long-term rewards, exploration, and frequently updated item.
05 Sep 2021 · 13 min · teardown recsys deeplearning
Bootstrapping Labels via ___ Supervision & Human-In-The-Loop
How to generate labels from scratch with semi, active, and weakly supervised learning.
01 Aug 2021 · 12 min · teardown machinelearning
System Design for Recommendations and Search
Breaking it into offline vs. online environments, and candidate retrieval vs. ranking steps.
27 Jun 2021 · 13 min · teardown production engineering recsys 🔥
Patterns for Personalization in Recommendations and Search
A whirlwind tour of bandits, embedding+MLP, sequences, graph, and user embeddings.
13 Jun 2021 · 25 min · teardown recsys machinelearning deeplearning
Search: Query Matching via Lexical, Graph, and Embedding Methods
An overview and comparison of the various approaches, with examples from industry search systems.
25 Apr 2021 · 21 min · teardown machinelearning production 🔥
Feature Stores: A Hierarchy of Needs
Access, serving, integrity, convenience, autopilot; use what you need.
21 Feb 2021 · 19 min · teardown machinelearning engineering 🔥
Real-time Machine Learning For Recommendations
Why real-time? How have China & US companies built them? How to design & build an MVP?
10 Jan 2021 · 21 min · teardown machinelearning recsys production 🔥
Data Discovery Platforms and Their Open Source Solutions
What questions do they answer? How do they compare? What open-source solutions are available?
25 Oct 2020 · 16 min · teardown datascience engineering 🔥
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