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How to Build and Monitor Systems Using Airflow?

Analytics Vidhya

Imagine scheduling your ML tasks to run automatically without the need for manual […] The post How to Build and Monitor Systems Using Airflow? Airflow can help you manage your workflow and make your life easier with its monitoring and notifications features. appeared first on Analytics Vidhya.

Systems 214
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Build faster with Buck2: Our open source build system

Engineering at Meta

Buck2, our new open source, large-scale build system , is now available on GitHub. Buck2 is an extensible and performant build system written in Rust and designed to make your build experience faster and more efficient. In our internal tests at Meta, we observed that Buck2 completed builds 2x as fast as Buck1.

Building 145
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Building a Recommendation System with Hugging Face Transformers

KDnuggets

Learn how to build the recommendation system with advanced technology.

Systems 141
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Zenlytic Is Building You A Better Coworker With AI Agents

Data Engineering Podcast

Summary The purpose of business intelligence systems is to allow anyone in the business to access and decode data to help them make informed decisions. The team at Zenlytic have leaned on the promise of large language models to build an AI agent that lets you converse with your data. Are data agents harder to build?

Building 278
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Entity Resolution: Your Guide to Deciding Whether to Build It or Buy It

This will help you decide whether to build an in-house entity resolution system or utilize an existing solution like the Senzing® API for entity resolution. This guide will walk you through the requirements and challenges of implementing entity resolution.

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A Tour Around Buck2, Meta's New Build System

Tweag

Buck2 is a from-scratch rewrite of Buck , a polyglot, monorepo build system that was developed and used at Meta (Facebook), and shares a few similarities with Bazel. As you may know, the Scalable Builds Group at Tweag has a strong interest in such scalable build systems. Bazel recording steps: 1.

Systems 141
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Building cost effective data pipelines with Python & DuckDB

Start Data Engineering

Building efficient data pipelines with DuckDB 4.1. Distributed systems are scalable, resilient to failures, & designed for high availability 4.5. Introduction 2. Project demo 3. Use DuckDB to process data, not for multiple users to access data 4.2. Cost calculation: DuckDB + Ephemeral VMs = dirt cheap data processing 4.3.

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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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LLMs in Production: Tooling, Process, and Team Structure

Speaker: Dr. Greg Loughnane and Chris Alexiuk

However, during development – and even more so once deployed to production – best practices for operating and improving generative AI applications are less understood. Register today to save your seat! December 6th, 2023 at 11:00am PST, 2:00pm EST, 7:pm GMT

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Improving the Accuracy of Generative AI Systems: A Structured Approach

Speaker: Anindo Banerjea, CTO at Civio & Tony Karrer, CTO at Aggregage

The number of use cases/corner cases that the system is expected to handle essentially explodes. 💥 Anindo Banerjea is here to showcase his significant experience building AI/ML SaaS applications as he walks us through the current problems his company, Civio, is solving.