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Building DoorDash’s Product Knowledge Graph with Large Language Models

DoorDash Engineering

DoorDash’s retail catalog is a centralized dataset of essential product information for all products sold by new verticals merchants – merchants operating a business other than a restaurant, such as a grocery, a convenience store, or a liquor store. Better personalization.

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Managing Model Drift in Production with MLOps

KDnuggets

MLOps for model drift management: Learn about ensuring the accuracy and performance of machine learning models in production.

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Column-Level Lineage, Model Performance, and Recommendations: ship trusted data products with dbt Explorer

dbt Developer Hub

We, as data professionals, have poured ourselves into raising happy healthy data products, and we should be proud of the insights they’ve driven. dbt Explorer centralizes documentation, lineage, and execution metadata to reduce the work required to ship trusted data products faster. What’s in a data platform? Ok but is it fresh?

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Common Sense Product Recommendations using Large Language Models

databricks

Product recommendations are a core feature of. Check out our LLM Solution Accelerators for Retail for more details and to download the notebooks.

Retail 81
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The Definitive Guide to Predictive Analytics

No wonder predictive analytics is now the #1 feature on product roadmaps. The Definitive Guide to Predictive Analytics has everything you need to get started, including real-world examples, steps to build your models, and solutions to common data challenges. How to price and package predictive analytics with your product.

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Feature Store Summit 2023: Practical Strategies for Deploying ML Models in Production Environments

KDnuggets

On October 11th, 2023 the Feature Store Summit will bring together leading ML companies, such as Uber, WeChat and more, for in-depth discussions about data and AI.

Data 129
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Prioritizing Data Science Models for Production

KDnuggets

Statistical performance metrics aren’t enough to pick the right models to bring to market.

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How to Package and Price Embedded Analytics

Just by embedding analytics, application owners can charge 24% more for their product. This framework explains how application enhancements can extend your product offerings. How much value could you add? Brought to you by Logi Analytics.

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Monetizing Analytics Features: Why Data Visualizations Will Never Be Enough

Think your customers will pay more for data visualizations in your application? Five years ago they may have. But today, dashboards and visualizations have become table stakes. Discover which features will differentiate your application and maximize the ROI of your embedded analytics. Brought to you by Logi Analytics.

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New Study: 2018 State of Embedded Analytics Report

Why do some embedded analytics projects succeed while others fail? We surveyed 500+ application teams embedding analytics to find out which analytics features actually move the needle. Read the 6th annual State of Embedded Analytics Report to discover new best practices. Brought to you by Logi Analytics.