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Azure Machine Learning – Empowering Your Data Science Journey

How to Learn Machine Learning

Welcome to this comprehensive guide on Azure Machine Learning , Microsoft’s powerful cloud-based platform that’s revolutionizing how organizations build, deploy, and manage machine learning models. Sit back, relax, and enjoy this exploration of Azure Machine Learning’s capabilities, benefits, and practical applications.

Azure 52
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Learn AI Together — Towards AI Community Newsletter #18

Towards AI

This week, I’m super excited to announce that we are finally releasing our book, ‘Building AI for Production; Enhancing LLM Abilities and Reliability with Fine-Tuning and RAG,’ where we gathered all our learnings. Building an Enterprise Data Lake with Snowflake Data Cloud & Azure using the SDLS Framework.

AI 97
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Introduction to Power BI Datamarts

ODSC - Open Data Science

The Datamarts capability opens endless possibilities for organizations to achieve their data analytics goals on the Power BI platform. This article is an excerpt from the book Expert Data Modeling with Power BI, Third Edition by Soheil Bakhshi, a completely updated and revised edition of the bestselling guide to Power BI and data modeling.

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What Are The Best Third-Party Data Ingestion Tools For Snowflake?

phData

If using a network policy with Snowflake, be sure to add Fivetran’s IP address list , which will ensure Azure Data Factory (ADF) Azure Data Factory is a fully managed, serverless data integration service built by Microsoft. Data Collector can use Snowflake’s native Snowpipe in its pipelines.

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MLOps and DevOps: Why Data Makes It Different

O'Reilly Media

Adapted from the book Effective Data Science Infrastructure. Data is at the core of any ML project, so data infrastructure is a foundational concern. ML use cases rarely dictate the master data management solution, so the ML stack needs to integrate with existing data warehouses.

ML 145
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What Can AI Teach Us About Data Centers? Part 1: Overview and Technical Considerations

ODSC - Open Data Science

Co-location data centers: These are data centers that are owned and operated by third-party providers and are used to house the IT equipment of multiple organizations. Edge data centers: These are data centers that are located closer to the edge of the network, where data is generated and consumed, rather than in central locations.

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The Evolution of Customer Data Modeling: From Static Profiles to Dynamic Customer 360

phData

Activity Schema Modeling: Capturing the Customer Journey in Action Now that we’ve got our Lego blocks of customer data, let’s talk about another game-changing approach that’s shaking up the world of customer data modeling: Activity Schema Modeling. It’s like having a universal translator for your customer data.