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  • 1
    Language: English
    Pages: 1 online resource (1 video file (3 hr., 39 min.)) , sound, color.
    Edition: [First edition].
    DDC: 006.3/1
    Keywords: Machine learning ; Cloud computing ; Instructional films ; Nonfiction films ; Internet videos
    Abstract: Enterprise MLOps Interviews Learn Enterprise MLOps from the experts This video series interviews the experts at MLOps to learn how to use MLOps to build and deploy ML models. Interviews Include: Introduction GPT-3: O'Reilly authors Shubham Saboo and Sandra Kublik: I talk with the authors of the new O'Reilly book GPT-3 about a range of topics, including why they wrote the book. Conversation with Piero Molino and Ludwig/Predibase: Detailed conversation about Declarative AutoML with Piero Molino, author of Ludwig and co-founder Predibase. Asaf Somekh, CEO Iguazio: Talk at Duke MIDS MLOps Course: Life of a Model (or the brutal reality of applying ML in enterprises and how to deal with it). Javier Luraschi and Pedro Luraschi, Co-Founders of Hal9.ai: Discuss MLOps with Javascript, including no-code and low-code approaches and Tensorflow.js. Topics Covered Include: Enterprise MLOps MLOps MLOps on AWS MLOps on GCP MLOps on Azure MLOps and DevOps MLOps with Ludwig Additional Popular Resources Pytest Master Class AWS Solutions Architect Professional Course Github Actions and GitOps in One Hour Video Course Jenkins CI/CD and Github in One Hour Video Course AWS Certified Cloud Practitioner Video Course Advanced Testing with Pytest Video Course AWS Solutions Architect Certification In ONE HOUR Python for DevOps Master Class 2022: CI/CD, Github Actions, Containers, and Microservices MLOPs Foundations: Chapter 2 Walkthrough of Practical MLOps Learn Docker containers in One Hour Video Course Introduction to MLOps Walkthrough AZ-900 (Azure Fundamentals) Quick reference guide 52 Weeks of AWS Episode 8: Infrastructure as Code with CDK and AWS Lambda Learn GCP Cloud Functions in One Hour Video Course Python Devops in TWO HOURS! MLOps Platforms From Zero: DatMLOps Platforms From Zero: Databricks, MLFlow/MLRun/SKLearn AWS Machine Learning Certification In ONE HOUR Fast, documented Machine Learning APIs with FastAPI Zero to One: AWS Lambda with SAM and Python in One Hour AWS Storage Solutions 2022: EBS/S3/EFS/Glacier Python Bootcamp for Data Testing In Python book Minimal Python book Practical MLOps book Python for DevOps-Playlist.
    Note: Online resource; title from title details screen (O'Reilly, viewed August 9, 2022)
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  • 2
    Online Resource
    Online Resource
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (293 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: If you’re like most R users, you have deep knowledge and love for statistics. But as your organization continues to collect huge amounts of data, adding tools such as Apache Spark makes a lot of sense. With this practical book, data scientists and professionals working with large-scale data applications will learn how to use Spark from R to tackle big data and big compute problems. Authors Javier Luraschi, Kevin Kuo, and Edgar Ruiz show you how to use R with Spark to solve different data analysis problems. This book covers relevant data science topics, cluster computing, and issues that should interest even the most advanced users. Analyze, explore, transform, and visualize data in Apache Spark with R Create statistical models to extract information and predict outcomes; automate the process in production-ready workflows Perform analysis and modeling across many machines using distributed computing techniques Use large-scale data from multiple sources and different formats with ease from within Spark Learn about alternative modeling frameworks for graph processing, geospatial analysis, and genomics at scale Dive into advanced topics including custom transformations, real-time data processing, and creating custom Spark extensions
    Note: Online resource; Title from title page (viewed October 11, 2019)
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  • 3
    Online Resource
    Online Resource
    [Erscheinungsort nicht ermittelbar] : China Machine Press | Boston, MA : Safari
    ISBN: 9787111661016
    Language: English , Chinese
    Pages: 1 online resource (262 pages)
    Edition: 1st edition
    Keywords: Electronic books
    Abstract: 如果你和大多数R语言用户一样,那你肯定喜欢统计学,也能够深入理解统计学。但是随着组织内部不断收集大量数据,添加Apache Spark这类工具就变得理所当然。在本书中,数据科学家和使用大规模数据应用的专业人员会学到如何使用Spark和R解决大数据和大计算问题。 作者会展示如何将Spark和R结合起来进行大数据分析。本书涵盖相关的数据科学话题、聚类计算,以及高级用户会感兴趣的问题。 在Apache Spark环境下,使用R来分析、探索、转换、可视化数据。 构建统计模型来提取信息并预测输出,自动化生产级的工作流程。 使用分布式计算技术在多台机器上进行分析和建模。 轻松使用Spark处理多个数据源和格式的大规模数据。 学习其他用于大规模图处理、地理空间分析和基因组学分析的建模框架。 深入高级话题,包括定制转换、实时数据处理和创建定制化Spark扩展。
    Note: Online resource; Title from title page (viewed July 1, 2020) , Mode of access: World Wide Web.
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