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Bringing More AI to Snowflake, the Data Cloud

DataRobot Blog

Integrating different systems, data sources, and technologies within an ecosystem can be difficult and time-consuming, leading to inefficiencies, data silos, broken machine learning models, and locked ROI. Exploratory Data Analysis After we connect to Snowflake, we can start our ML experiment.

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The AI Process

Towards AI

Last Updated on August 17, 2023 by Editorial Team Author(s): Jeff Holmes MS MSCS Originally published on Towards AI. Jason Leung on Unsplash AI is still considered a relatively new field, so there are really no guides or standards such as SWEBOK. 85% or more of AI projects fail [1][2]. 85% or more of AI projects fail [1][2].

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LLMOps demystified: Why it’s crucial and best practices for 2023

Data Science Dojo

From data management to model fine-tuning, LLMOps ensures efficiency, scalability, and risk mitigation. As LLMs redefine AI capabilities, mastering LLMOps becomes your compass in this dynamic landscape. Some projects may necessitate a comprehensive LLMOps approach, spanning tasks from data preparation to pipeline production.

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Introducing our New Book: Implementing MLOps in the Enterprise

Iguazio

Drawing from their extensive experience in the field, the authors share their strategies, methodologies, tools and best practices for designing and building a continuous, automated and scalable ML pipeline that delivers business value. The book contains a full chapter dedicated to generative AI.

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Accelerate time to business insights with the Amazon SageMaker Data Wrangler direct connection to Snowflake

AWS Machine Learning Blog

Amazon SageMaker Data Wrangler is a single visual interface that reduces the time required to prepare data and perform feature engineering from weeks to minutes with the ability to select and clean data, create features, and automate data preparation in machine learning (ML) workflows without writing any code.

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Building ML Platform in Retail and eCommerce

The MLOps Blog

And eCommerce companies have a ton of use cases where ML can help. The problem is, with more ML models and systems in production, you need to set up more infrastructure to reliably manage everything. And because of that, many companies decide to centralize this effort in an internal ML platform. But how to build it?

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Access Snowflake data using OAuth-based authentication in Amazon SageMaker Data Wrangler

Flipboard

Snowflake is an AWS Partner with multiple AWS accreditations, including AWS competencies in machine learning (ML), retail, and data and analytics. Data scientist experience In this section, we cover how data scientists can connect to Snowflake as a data source in Data Wrangler and prepare data for ML.

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