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Titlebook: Databricks Data Intelligence Platform; Unlocking the GenAI Nikhil Gupta,Jason Yip Book 2024 The Editor(s) (if applicable) and The Author(s

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樓主
發(fā)表于 2025-3-21 16:22:30 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Databricks Data Intelligence Platform
副標(biāo)題Unlocking the GenAI
編輯Nikhil Gupta,Jason Yip
視頻videohttp://file.papertrans.cn/285/284475/284475.mp4
概述First comprehensive guide to end-to-end Databrick Intellifence Platform.Build Gen AI Applications plus Data Applications from Data Ingestion to Model Serving and Dashboards.Insider best practices and
圖書封面Titlebook: Databricks Data Intelligence Platform; Unlocking the GenAI Nikhil Gupta,Jason Yip Book 2024 The Editor(s) (if applicable) and The Author(s
描述.This book is your comprehensive guide to building robust Generative AI solutions using the Databricks Data Intelligence Platform. Databricks is the fastest-growing data platform offering unified analytics and AI capabilities within a single governance framework, enabling organizations to streamline their data processing workflows, from ingestion to visualization. Additionally, Databricks provides features to train a high-quality large language model (LLM), whether you are looking for Retrieval-Augmented Generation (RAG) or fine-tuning...?..Databricks offers a scalable and efficient solution for processing large volumes of both structured and unstructured data, facilitating advanced analytics, machine learning, and real-time processing. In today‘s GenAI world, Databricks plays a crucial role in empowering organizations to extract value from their data effectively, driving innovation and gaining a competitive edge in the digital age. This book will not only help you master the Data Intelligence Platform but also help power your enterprise to the next level with a bespoke LLM unique to your organization...?..Beginning with foundational principles, the book starts with a platform over
出版日期Book 2024
關(guān)鍵詞Lakehouse; Databricks; Database; data Intelligence Platform; Data Engineering; Machine learniing; GenAI; LL
版次1
doihttps://doi.org/10.1007/979-8-8688-0444-1
isbn_softcover979-8-8688-0443-4
isbn_ebook979-8-8688-0444-1
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to APress Media, LLC, part
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書目名稱Databricks Data Intelligence Platform影響因子(影響力)




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書目名稱Databricks Data Intelligence Platform網(wǎng)絡(luò)公開度




書目名稱Databricks Data Intelligence Platform網(wǎng)絡(luò)公開度學(xué)科排名




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書目名稱Databricks Data Intelligence Platform被引頻次學(xué)科排名




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沙發(fā)
發(fā)表于 2025-3-21 21:00:23 | 只看該作者
http://image.papertrans.cn/e/image/284475.jpg
板凳
發(fā)表于 2025-3-22 02:40:00 | 只看該作者
https://doi.org/10.1007/979-8-8688-0444-1Lakehouse; Databricks; Database; data Intelligence Platform; Data Engineering; Machine learniing; GenAI; LL
地板
發(fā)表于 2025-3-22 06:38:42 | 只看該作者
5#
發(fā)表于 2025-3-22 08:59:02 | 只看該作者
The intensifying pace of digital transformation has led companies to amass increasing volumes of diverse data from various sources. This data explosion carries enormous potential for organizations to uncover transformative insights to guide innovation and decision-making through advanced analytics.
6#
發(fā)表于 2025-3-22 13:34:35 | 只看該作者
Fazit: Die Identit?t des Star Wars FansIt is no secret that good, reliable data is the foundation of the lakehouse architecture. Organizations need clean, fresh, and reliable data to drive their analytics and data science projects, which in turn help them make decisions for key business initiatives.
7#
發(fā)表于 2025-3-22 19:04:13 | 只看該作者
8#
發(fā)表于 2025-3-22 22:20:25 | 只看該作者
Victoria Schwenzer,Nicole SelmerDatabricks not only provides exceptional data processing capabilities but also offers a wealth of opportunities to develop machine learning use cases.
9#
發(fā)表于 2025-3-23 04:36:23 | 只看該作者
,Ernst Nolte’s Theory of Fascism,This chapter starts by understanding the concept of continuous integration/continuous deployment (CI/CD). Then we will move into Databricks repos and see how we can connect external Git repos to the Databricks workspace and illustrate the CI/CD process with regard to Databricks.
10#
發(fā)表于 2025-3-23 08:09:57 | 只看該作者
https://doi.org/10.1007/978-3-662-64469-0In this chapter, we will look into how pricing for running workloads on Databricks works. It is important to be able to calculate the costs involved in running solutions on Databricks. We will see what factors determine the pricing model and recommend which compute SKU should be used for running your specific workloads.
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