標(biāo)題: Titlebook: Databricks Data Intelligence Platform; Unlocking the GenAI Nikhil Gupta,Jason Yip Book 2024 The Editor(s) (if applicable) and The Author(s [打印本頁(yè)] 作者: Traction 時(shí)間: 2025-3-21 16:22
書目名稱Databricks Data Intelligence Platform影響因子(影響力)
書目名稱Databricks Data Intelligence Platform影響因子(影響力)學(xué)科排名
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
書目名稱Databricks Data Intelligence Platform被引頻次
書目名稱Databricks Data Intelligence Platform被引頻次學(xué)科排名
書目名稱Databricks Data Intelligence Platform年度引用
書目名稱Databricks Data Intelligence Platform年度引用學(xué)科排名
書目名稱Databricks Data Intelligence Platform讀者反饋
書目名稱Databricks Data Intelligence Platform讀者反饋學(xué)科排名
作者: Employee 時(shí)間: 2025-3-21 21:00
http://image.papertrans.cn/e/image/284475.jpg作者: 哭得清醒了 時(shí)間: 2025-3-22 02:40
https://doi.org/10.1007/979-8-8688-0444-1Lakehouse; Databricks; Database; data Intelligence Platform; Data Engineering; Machine learniing; GenAI; LL作者: 追逐 時(shí)間: 2025-3-22 06:38 作者: Mediocre 時(shí)間: 2025-3-22 08:59
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.作者: 最低點(diǎn) 時(shí)間: 2025-3-22 13:34
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.作者: 最低點(diǎn) 時(shí)間: 2025-3-22 19:04 作者: morale 時(shí)間: 2025-3-22 22:20
Victoria Schwenzer,Nicole SelmerDatabricks not only provides exceptional data processing capabilities but also offers a wealth of opportunities to develop machine learning use cases.作者: packet 時(shí)間: 2025-3-23 04:36
,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.作者: Ige326 時(shí)間: 2025-3-23 08:09
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.作者: DAMN 時(shí)間: 2025-3-23 10:12
In this chapter, we will walk through creating a healthcare and life science application from start to finish. The input is some realistic patient data, but this data was generated by a high-quality data generator, so there are no privacy concerns in this scenario.作者: 紅腫 時(shí)間: 2025-3-23 15:57
Databricks Platform: From Lakehouse to Data Intelligence Platform,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.作者: debble 時(shí)間: 2025-3-23 20:53 作者: 向下 時(shí)間: 2025-3-24 01:42 作者: Oversee 時(shí)間: 2025-3-24 03:03
Machine Learning Operations Using Databricks,Databricks not only provides exceptional data processing capabilities but also offers a wealth of opportunities to develop machine learning use cases.作者: Factual 時(shí)間: 2025-3-24 06:46 作者: 打包 時(shí)間: 2025-3-24 12:30 作者: Disk199 時(shí)間: 2025-3-24 15:01 作者: 柳樹；枯黃 時(shí)間: 2025-3-24 21:12 作者: 與野獸博斗者 時(shí)間: 2025-3-24 23:55 作者: conflate 時(shí)間: 2025-3-25 06:17
DBRX: Creating an LLM from Scratch Using Databricks,ned from scratch on the Databricks and MosaicML platforms. At the time of model release, it outperformed established open-source models on language understanding (MMLU), programming (HumanEval), and math (GSM8K), as shown in Figure 13-1.作者: Melodrama 時(shí)間: 2025-3-25 10:52
Extension and Generalizations of Fairness,icks platform and set the stage for deep dives into various product features in later chapters. Initially, you will learn about the most common terms unique to the Databricks platform. After that you will learn about Databricks compute (clusters) and Databricks notebooks. Again, this chapter acts as作者: elucidate 時(shí)間: 2025-3-25 11:47
https://doi.org/10.1007/978-3-319-30563-9 like Hadoop systems, ERP/CRM systems, or real-time streaming sources. A significant number of analytics use cases need to not only process this data efficiently but also do it in a unified manner to produce meaningful reports and predictions. So to start this journey, organizations need to ingest d作者: Lipohypertrophy 時(shí)間: 2025-3-25 19:27 作者: 收養(yǎng) 時(shí)間: 2025-3-25 21:18
ed regarding quality, management, and ownership. Organizations today, especially with ever-expanding use cases for GenAI, face expanding data privacy regulations. Nonetheless, the reliance on data is increasing as organizations look to help optimize operations and drive business decision-making. The作者: filial 時(shí)間: 2025-3-26 00:52 作者: PLUMP 時(shí)間: 2025-3-26 06:42
Victoria Schwenzer,Nicole Selmerhat exactly is GenAI, and how does Databricks come into the picture? And how it can help organizations deploy their own chatbot or develop their own GenAI applications? In this chapter, we will first learn the concepts around GenAI. Then we will discuss how Databricks and the newly acquired company 作者: 審問,審訊 時(shí)間: 2025-3-26 10:24
From Electricity to Natural Philosophy,LLM) operations. This chapter has certain similarities with the chapter on generative AI (GenAI), but we will mainly focus on the operations part of machine learning and the benefits of it as a practice. We will also dive deep into using different techniques and libraries in the industry to perform 作者: biosphere 時(shí)間: 2025-3-26 14:12
Norbert Welsch,Claus Chr Liebmannile most applications allow you to build a bot or GPT very easily, enterprises are looking for ways to evaluate the quality of the chatbot. This is where the AI Agent Framework comes in. We will not only discuss how to deploy a chatbot from end to end, but how to evaluate it with an LLM as a Judge o作者: Solace 時(shí)間: 2025-3-26 17:41
Norbert Welsch,Claus Chr. Liebmannned from scratch on the Databricks and MosaicML platforms. At the time of model release, it outperformed established open-source models on language understanding (MMLU), programming (HumanEval), and math (GSM8K), as shown in Figure 13-1.作者: Pedagogy 時(shí)間: 2025-3-27 00:22
International Political Economy Seriesith Unity Catalog providing a single governance layer and Databricks providing features to enable all use cases such as data engineering, data science, streaming, and warehousing. With the advent and popularity of GenAI and LLMs since 2023, Databricks has integrated them into its platform. The Datab作者: justify 時(shí)間: 2025-3-27 04:34
Detailprinzipien und Toleranzen,ive into topics like VNET injection and No Public IP (NPIP). Further, we will look into encryption and access control features. Finally, we will review an important tool called Security Analysis Tool developed by Databricks, which, when executed on a Databricks workspace, helps identify gaps in work作者: 動(dòng)作謎 時(shí)間: 2025-3-27 08:34 作者: Abrade 時(shí)間: 2025-3-27 12:10 作者: 誓言 時(shí)間: 2025-3-27 14:55
From Electricity to Natural Philosophy,LLM) operations. This chapter has certain similarities with the chapter on generative AI (GenAI), but we will mainly focus on the operations part of machine learning and the benefits of it as a practice. We will also dive deep into using different techniques and libraries in the industry to perform these operations, which Databricks also supports.作者: 不舒服 時(shí)間: 2025-3-27 20:57
Norbert Welsch,Claus Chr. Liebmannned from scratch on the Databricks and MosaicML platforms. At the time of model release, it outperformed established open-source models on language understanding (MMLU), programming (HumanEval), and math (GSM8K), as shown in Figure 13-1.作者: 令人悲傷 時(shí)間: 2025-3-28 01:00 作者: landmark 時(shí)間: 2025-3-28 04:26 作者: semiskilled 時(shí)間: 2025-3-28 07:52 作者: Desert 時(shí)間: 2025-3-28 10:33
on top of cloud data lakes. Delta Lake is a storage protocol that exactly fits the requirements. Delta Lake is an open, performant storage format that enables organizations to build data lakehouses, allowing data warehousing and machine learning directly on the data lake.作者: 忍耐 時(shí)間: 2025-3-28 15:20
Victoria Schwenzer,Nicole SelmerenAI applications? In this chapter, we will first learn the concepts around GenAI. Then we will discuss how Databricks and the newly acquired company Mosaic ML will work together and transform the industry once more. This chapter lays some background regarding the journey of GenAI and introduces the Databricks offering in the GenAI space.作者: 糾纏,纏繞 時(shí)間: 2025-3-28 20:02 作者: projectile 時(shí)間: 2025-3-28 22:58
Detailprinzipien und Toleranzen,w an important tool called Security Analysis Tool developed by Databricks, which, when executed on a Databricks workspace, helps identify gaps in workspace security with recommended best practices and gives pointers to admins on how to resolve those deficiencies.作者: minimal 時(shí)間: 2025-3-29 03:21 作者: dialect 時(shí)間: 2025-3-29 09:11 作者: Obedient 時(shí)間: 2025-3-29 11:29 作者: 無可爭(zhēng)辯 時(shí)間: 2025-3-29 18:06
Delta Lake - Deep Dive, on top of cloud data lakes. Delta Lake is a storage protocol that exactly fits the requirements. Delta Lake is an open, performant storage format that enables organizations to build data lakehouses, allowing data warehousing and machine learning directly on the data lake.作者: 煩躁的女人 時(shí)間: 2025-3-29 22:15
Generative AI with Databricks,enAI applications? In this chapter, we will first learn the concepts around GenAI. Then we will discuss how Databricks and the newly acquired company Mosaic ML will work together and transform the industry once more. This chapter lays some background regarding the journey of GenAI and introduces the Databricks offering in the GenAI space.作者: 離開真充足 時(shí)間: 2025-3-30 02:30
Mosaic AI Agent Framework: Creating Quality AI Agents,ere the AI Agent Framework comes in. We will not only discuss how to deploy a chatbot from end to end, but how to evaluate it with an LLM as a Judge or human feedback. These metrics will ensure data scientists who are already familiar with MLflow will be able to transition to LLM evaluation easily.作者: Vulvodynia 時(shí)間: 2025-3-30 07:34
Databricks Platform Security and Compliance,w an important tool called Security Analysis Tool developed by Databricks, which, when executed on a Databricks workspace, helps identify gaps in workspace security with recommended best practices and gives pointers to admins on how to resolve those deficiencies.作者: 得體 時(shí)間: 2025-3-30 08:24
refore, they are looking for data governance on their data platforms to ensure that not only their data assets but, more importantly, their AI products are consistently developed and maintained and their precise guidelines and standards are adhered to.作者: anthropologist 時(shí)間: 2025-3-30 14:46 作者: Delirium 時(shí)間: 2025-3-30 17:05
Springer Tracts in Advanced Roboticsche Spark offers two popular streaming processing engines: Spark Streaming and Structured Streaming. While both engines are designed for real-time data processing, they have distinct architectures, advantages, and use cases.作者: Seminar 時(shí)間: 2025-3-30 20:42
Data Governance with Unity Catalog,refore, they are looking for data governance on their data platforms to ensure that not only their data assets but, more importantly, their AI products are consistently developed and maintained and their precise guidelines and standards are adhered to.作者: compel 時(shí)間: 2025-3-31 03:05 作者: 奴才 時(shí)間: 2025-3-31 07:00
Spark Structured Streaming: A Comprehensive Guide,che Spark offers two popular streaming processing engines: Spark Streaming and Structured Streaming. While both engines are designed for real-time data processing, they have distinct architectures, advantages, and use cases.作者: Hypopnea 時(shí)間: 2025-3-31 10:51
Book 2024gaining 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作者: 爭(zhēng)論 時(shí)間: 2025-3-31 14:16
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 over979-8-8688-0443-4979-8-8688-0444-1作者: Serenity 時(shí)間: 2025-3-31 19:47 作者: 無能力之人 時(shí)間: 2025-3-31 23:53
Data Ingestion in Lakehouse, like Hadoop systems, ERP/CRM systems, or real-time streaming sources. A significant number of analytics use cases need to not only process this data efficiently but also do it in a unified manner to produce meaningful reports and predictions. So to start this journey, organizations need to ingest d
