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The ML Observability Checklist

insideBIGDATA

This checklist from our friends over at Arize covers the essential elements to consider when evaluating an ML observability platform.

ML 221
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Analysis of Retail Data Insights With PySpark & Databricks

Analytics Vidhya

Introduction Data has become an essential part of our daily lives in today’s digital age. From searching for a product on e-commerce platforms to placing an order and receiving it at home, we are constantly generating and consuming data.

Analytics 268
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Crossing the demo-to-production chasm with Snorkel Custom

Snorkel AI

Today, I’m incredibly excited to announce our new offering, Snorkel Custom, to help enterprises cross the chasm from flashy chatbot demos to real production AI value. Enterprises are under mounting pressure to show value from AI investments, but are realizing that off-the-shelf LLMs are rarely enough to meet production requirements.

AI 80
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Relational Graph Convolutional Networks for Sentiment Analysis

Hacker News

With the growth of textual data across online platforms, sentiment analysis has become crucial for extracting insights from user-generated content. Our experiments highlight the effectiveness of RGCNs in capturing relational information for sentiment analysis tasks.

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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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How Meta built the infrastructure for Threads

Hacker News

On July 5, 2023, Meta launched Threads, the newest product in our family of apps, to an unprecedented success that saw it garner over 100 million sign ups in its first five days. The seamless scale that people experienced as they signed up by the millions came on the shoulders of over a decade of infrastructure and product development.

Database 179
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Natural user interface: Is the understanding between the human and the machine already here?

Dataconomy

To explore what the industry is heading towards here, I talked to one of the speakers at our Epic AI Dev Summit, Or Gorodissky, the Vice President of Research and Development at the D-ID company, the summit’s co-organizer. Alex: Integrating AI technologies into existing systems and platforms is often complex.

AI 218
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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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5 Early Indicators Your Embedded Analytics Will Fail

Many application teams leave embedded analytics to languish until something—an unhappy customer, plummeting revenue, a spike in customer churn—demands change. But by then, it may be too late. In this White Paper, Logi Analytics has identified 5 tell-tale signs your project is moving from “nice to have” to “needed yesterday.".

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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.