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How ML System Design helps us to make better ML products

Xebia

Table of Contents What is Machine Learning System Design? Design Process Clarify requirements Frame problem as an ML task Identify data sources and their availability Model development Serve predictions Observability Iterate on your design What is Machine Learning System Design?

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Building a Beautiful Data Lakehouse

CIO

Applying artificial intelligence (AI) to data analytics for deeper, better insights and automation is a growing enterprise IT priority. But the data repository options that have been around for a while tend to fall short in their ability to serve as the foundation for big data analytics powered by AI.

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Why Are There So Few Women in Computer Science?

The Crazy Programmer

According to the Guardian, top organizations like Google and Uber have only women engineers composing 20% of their IT workforce. Ada also designed a method through which analytical engines perform successful computations with the help of the machine designed and invented by her friend, Charles Babbage.

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What LinkedIn learned leveraging LLMs for its billion users

CIO

For LinkedIn, this was no different, as its road to LLM insights was anything but smooth, said LinkedIn’s Juan Bottaro, a principal software engineer and tech lead. As an example, Bottaro referenced the part of the system designed to understand intent. The initial deliverables “felt lacking,” Bottaro said.

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Automate emails for task management using Amazon Bedrock Agents, Amazon Bedrock Knowledge Bases, and Amazon Bedrock Guardrails

AWS Machine Learning - AI

High Level System Design The solution consists of the following components: Email service – This component manages incoming and outgoing customer emails, serving as the primary interface for email communications. AI-powered email processing engine – Central to the solution, this engine uses AI to analyze and process emails.

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Accelerating insurance policy reviews with generative AI: Verisk’s Mozart companion

AWS Machine Learning - AI

Verisk (Nasdaq: VRSK) is a leading strategic data analytics and technology partner to the global insurance industry, empowering clients to strengthen operating efficiency, improve underwriting and claims outcomes, combat fraud, and make informed decisions about global risks. Connect with him on LinkedIn.

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25 Feb Cloudera Federal Forum in Tysons Corner: Amazing agenda filled with lessons learned and best practices

CTOvision

This popular gathering is designed to enable dialogue about business and technical strategies to leverage today’s big data platforms and applications to your advantage. Big data and its effect on the transformative power of data analytics are undeniable. Chief Information Officer, Defense Information Systems Agency.