From 286c602d5e0beed2b7a6d7b4b4c43324e632d342 Mon Sep 17 00:00:00 2001 From: slweeb <91897291+slweeb@users.noreply.github.com> Date: Fri, 31 Mar 2023 21:16:54 -0400 Subject: [PATCH] Update README.md --- README.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index 056cc0770..ba9c02da0 100644 --- a/README.md +++ b/README.md @@ -22,10 +22,10 @@ These are the main components of the Recommendation Algorithm included in this r | | [user-tweet-entity-graph](src/scala/com/twitter/recos/user_tweet_entity_graph/README.md) (UTEG)| Maintains an in memory User to Tweet interaction graph, and finds candidates based on traversals of this graph. This is built on the [GraphJet](https://github.com/twitter/GraphJet) framework. Several other GraphJet based features and candidate sources are located [here](src/scala/com/twitter/recos) | | | [follow-recommendation-service](follow-recommendations-service/README.md) (FRS)| Provides Users with recommendations for accounts to follow, and Tweets from those accounts. | | Ranking | [light-ranker](src/python/twitter/deepbird/projects/timelines/scripts/models/earlybird/README.md) | Light ranker model used by search index (Earlybird) to rank Tweets. | -| | [heavy-ranker](https://github.com/twitter/the-algorithm-ml/blob/main/projects/home/recap/README.md) | Neural network for ranking candidate tweets. One of the main signals used to select timeline Tweets post candidate sourcing. | +| | [heavy-ranker](https://github.com/twitter/the-algorithm-ml/blob/main/projects/home/recap/README.md) | Neural network for ranking candidate Tweets. One of the main signals used to select timeline Tweets post candidate sourcing. | | Tweet mixing & filtering | [home-mixer](home-mixer/README.md) | Main service used to construct and serve the Home Timeline. Built on [product-mixer](product-mixer/README.md) | | | [visibility-filters](visibilitylib/README.md) | Responsible for filtering Twitter content to support legal compliance, improve product quality, increase user trust, protect revenue through the use of hard-filtering, visible product treatments, and coarse-grained downranking. | -| | [timelineranker](timelineranker/README.md) | Legacy service which provides relevance-scored tweets from the Earlybird Search Index and UTEG service. | +| | [timelineranker](timelineranker/README.md) | Legacy service which provides relevance-scored Tweets from the Earlybird Search Index and UTEG service. | | Software framework | [navi](navi/navi/README.md) | High performance, machine learning model serving written in Rust. | | | [product-mixer](product-mixer/README.md) | Software framework for building feeds of content. | | | [twml](twml/README.md) | Legacy machine learning framework built on TensorFlow v1. |