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![]() ![]() Ibrahim Haddad, the general manager of LF AI & Data, said in a press statement. “We’re excited to welcome Feathr to LF AI & Data and for it to be part of our technical project portfolio (41 projects and growing) with over 17K developers,” Dr. …and standardizes the workflow with a centralized repository for features (Image courtesy LinkedIn)īy donating Feathr to The Linux Foundatoin’s LF AI & Data group, LinkedIn is putting additional governance in place around the open source project, which should help attract more users and more contributors to the project. Feature stores also provide a more repeatable method for transforming source data into features (which is something not found in all feature stores), and boosts the performance of ML serving at the inference stage by centralizing the storage and serving of features. This allows the same features to be used multiple ML programs, improving productivity and accuracy. By defining the data features used in ML programs once in a common feature namespace, users can now pull them up “by name” from within ML workflows. The impetus in creating Feathr was providing greater consistency, accuracy, and performance in its machine learning programs. Instead of manually working with features as part of an individual data pipeline, Feathr automates and standardizes the interaction with the data type, which is used in both the training and inference stages of machine learning. LinkedIn today announced that its open source feature store, dubbed Feathr, is joining LF AI & Data, the Linux Foundation’s umbrella foundation for big data and AI projects.įeathr was originally developed at LinkedIn to help manage and serve features used in its machine learning applications. ![]()
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