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  • 1
    Online Resource
    Online Resource
    Inżynieria danych na platformie AWS : jak tworzyć kompletne potoki uczenia maszynowego (2021)
    Gliwice : Helion
    Details
    ISBN: 9788328391291 , 8328391295
    Language: Polish
    Pages: 1 online resource (472 pages) , illustrations
    Edition: [First edition].
    Uniform Title: Data science on AWS
    DDC: 006.3
    Keywords: Amazon Web Services (Firm) ; Machine learning ; Cloud computing ; Data mining ; Business Data processing ; Management Data processing
    Abstract: Platforma Amazon Web Services jest uważana za największą i najbardziej dojrzałą chmurę obliczeniową. Zapewnia bogaty zestaw specjalistycznych narzędzi ułatwiających realizację projektów z zakresu inżynierii danych i uczenia maszynowego. W ten sposób inżynierowie danych, architekci i menedżerowie mogą szybko zacząć używać danych do podejmowania kluczowych decyzji biznesowych. Uzyskanie optymalnej efektywności pracy takich projektów wymaga jednak dobrego rozeznania w możliwościach poszczególnych narzędzi, usług i bibliotek. Dzięki temu praktycznemu przewodnikowi szybko nauczysz się tworzyć i uruchamiać procesy w chmurze, a następnie integrować wyniki z aplikacjami. Zapoznasz się ze scenariuszami stosowania technik sztucznej inteligencji: przetwarzania języka naturalnego, rozpoznawania obrazów, wykrywania oszustw, wyszukiwania kognitywnego czy wykrywania anomalii w czasie rzeczywistym. Ponadto dowiesz się, jak łączyć cykle rozwoju modeli z pobieraniem i analizą danych w powtarzalnych potokach MLOps. W książce znajdziesz też zbiór technik zabezpieczania projektów i procesów z obszaru inżynierii danych, takich jak stosowanie usługi IAM, uwierzytelnianie, autoryzacja, izolacja sieci, szyfrowanie danych w spoczynku czy postkwantowe szyfrowanie sieci dla danych w tranzycie.
    URL: lizenzpflichtig
    Library Location Call Number Volume/Issue/Year Availability
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    Online Resource
    MPI Ethno. Forsch.
  • 2
    Online Resource
    Online Resource
    GENERATIVE AI ON AWS : building context-aware multimodal reasoning applications (2023)
    [Sebastopol, California] : O'Reilly Media, Inc.
    Details
    ISBN: 9781098159191 , 1098159195
    Language: English
    Pages: 1 online resource
    Edition: First edtion.
    Parallel Title: Erscheint auch als
    DDC: 006.3
    Keywords: Amazon Web Services (Firm) ; Artificial intelligence Computer programs ; Application software
    Abstract: Companies today are moving rapidly to integrate generative AI into their products and services. But there's a great deal of hype (and misunderstanding) about the impact and promise of this technology. With this book, Chris Fregly, Antje Barth, and Shelbee Eigenbrode from AWS help CTOs, ML practitioners, application developers, business analysts, data engineers, and data scientists find practical ways to use this exciting new technology. You'll learn the generative AI project life cycle including use case definition, model selection, model fine-tuning, retrieval-augmented generation, reinforcement learning from human feedback, and model quantization, optimization, and deployment. And you'll explore different types of models including large language models (LLMs) and multimodal models such as Stable Diffusion for generating images and Flamingo/IDEFICS for answering questions about images. Apply generative AI to your business use cases Determine which generative AI models are best suited to your task Perform prompt engineering and in-context learning Fine-tune generative AI models on your datasets with low-rank adaptation (LoRA) Align generative AI models to human values with reinforcement learning from human feedback (RLHF) Augment your model with retrieval-augmented generation (RAG) Explore libraries such as LangChain and ReAct to develop agents and actions Build generative AI applications with Amazon Bedrock.
    URL: lizenzpflichtig
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    Online Resource
    MPI Ethno. Forsch.
  • 3
    Online Resource
    Online Resource
    Data Science on AWS (2021)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (122 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: If you use data to make critical business decisions, this book is for you. Whether you're a data analyst, research scientist, data engineer, ML engineer, data scientist, application developer, or systems developer, this guide helps you broaden your understanding of the modern data science stack, create your own machine learning pipelines, and deploy them to applications at production scale. The AWS data science stack unifies data science, data engineering, and application development to help you level up your skills beyond your current role. Authors Antje Barth and Chris Fregly show you how to build your own ML pipelines from existing APIs, submit them to the cloud, and integrate results into your application in minutes instead of days. Innovate quickly and save money with AWS's on-demand, serverless, and cloud-managed services Implement open source technologies such as Kubeflow, Kubernetes, TensorFlow, and Apache Spark on AWS Build and deploy an end-to-end, continuous ML pipeline with the AWS data science stack Perform advanced analytics on at-rest and streaming data with AWS and Spark Integrate streaming data into your ML pipeline for continuous delivery of ML models using AWS and Apache Kafka
    Note: Online resource; Title from title page (viewed July 25, 2021) , Mode of access: World Wide Web.
    URL: lizenzpflichtig
    Library Location Call Number Volume/Issue/Year Availability
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    Online Resource
    MPI Ethno. Forsch.
  • 4
    Online Resource
    Online Resource
    O’Reilly Radar : Data & AI (2021)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (1 video file, approximately 6 hr., 52 min.)
    Edition: 1st edition
    Keywords: Electronic videos
    Abstract: O’Reilly Radar: Data & AI will showcase what’s new, what’s important, and what’s coming in the field. It includes two keynotes and two concurrent three-hour tracks—designed to lay out for tech leaders the issues, tools, and best practices that are critical to an organization at any step of their data and AI journey. You’ll explore everything from prototyping and pipelines to deployment and DevOps to responsible and ethical AI.
    Note: Online resource; Title from title screen (viewed October 14, 2021) , Mode of access: World Wide Web.
    URL: lizenzpflichtig
    Library Location Call Number Volume/Issue/Year Availability
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    Online Resource
    MPI Ethno. Forsch.
  • 5
    Online Resource
    Online Resource
    Data Science mit AWS : end-to-end pipelines für continuous machine learning implementieren (2022)
    Heidelberg : dpunkt
    Details
    Language: German
    Pages: 1 online resource (550 pages) , illustrations
    Edition: 1. Auflage.
    Uniform Title: Data science on AWS
    DDC: 006.3/1
    Keywords: Amazon Web Services (Firm) ; Machine learning ; Cloud computing ; Web services ; Artificial intelligence ; Artificial Intelligence ; Apprentissage automatique ; Infonuagique ; Services Web ; Intelligence artificielle ; artificial intelligence ; Electronic books
    Abstract: Mit diesem Buch lernen Machine-Learning- und KI-Praktiker, wie sie erfolgreich Data-Science-Projekte mit Amazon Web Services erstellen und in den produktiven Einsatz bringen. Es bietet einen detaillierten Einblick in den KI- und Machine-Learning-Stack von Amazon, der Data Science, Data Engineering und Anwendungsentwicklung vereint. Chris Fregly und Antje Barth beschreiben verständlich und umfassend, wie Sie das breite Spektrum an AWS-Tools nutzbringend für Ihre ML-Projekte einsetzen. Der praxisorientierte Leitfaden zeigt Ihnen konkret, wie Sie ML-Pipelines in der Cloud erstellen und die Ergebnisse dann innerhalb von Minuten in Anwendungen integrieren. Sie erfahren, wie Sie alle Teilschritte eines Workflows zu einer wiederverwendbaren MLOps-Pipeline bündeln, und Sie lernen zahlreiche reale Use Cases zum Beispiel aus den Bereichen Natural Language Processing, Computer Vision oder Betrugserkennung kennen. Im gesamten Buch wird zudem erläutert, wie Sie Kosten senken und die Performance Ihrer Anwendungen optimieren können.
    Note: Includes bibliographical references and index
    URL: lizenzpflichtig
    Library Location Call Number Volume/Issue/Year Availability
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    Online Resource
    MPI Ethno. Forsch.
  • 6
    Online Resource
    Online Resource
    Jissen AWS dēta saiensu : endo tsū endo no MLOps paipurain jissō (2021)
    Tōkyō-to Shinjuku-ku : Orairī Japan
    Details
    Orig.schr. Ausgabe: 初版.
    Title: 実践AWSデータサイエンス : : エンドツーエンドのMLOpsパイプライン実装 /
    Publisher: オライリー・ジャパン,
    ISBN: 9784873119687 , 4873119685
    Language: Japanese
    Pages: 1 online resource (570 pages)
    Edition: Shohan.
    Uniform Title: Data science on AWS
    DDC: 004.6782
    Keywords: Amazon Web Services (Firm) ; Machine learning ; Cloud computing ; Data mining ; Business Data processing ; Management Data processing ; Amazon Web Services (Firm) ; Business ; Data processing ; Cloud computing ; Data mining ; Machine learning ; Management ; Data processing
    Note: In Japanese.
    URL: lizenzpflichtig
    Library Location Call Number Volume/Issue/Year Availability
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    Online Resource
    MPI Ethno. Forsch.
  • 7
    Online Resource
    Online Resource
    GenAI superstream : Possibilities and pitfalls (2024)
    [Place of publication not identified] : O'Reilly Media, Inc.
    Details
    Language: English
    Pages: 1 online resource (1 video file (3 hr., 34 min.)) , sound, color.
    Edition: [First edition].
    DDC: 006.3
    Keywords: Artificial intelligence ; Intelligence artificielle ; artificial intelligence ; Instructional films ; Nonfiction films ; Internet videos ; Films de formation ; Films autres que de fiction ; Vidéos sur Internet
    Abstract: Artificial intelligence promises to augment human capabilities, revolutionize scientific research, personalize consumer experiences, transform education, and usher in an era of autonomous transportation. But companies should understand the risks along with the potential. Implementing AI without clear use cases or business goals can lead to wasted resources, and a lack of expertise or attention to ethical considerations can bring powerful consequences. Join our experts to explore how AI is changing technology and business. You'll learn how to harness its transformative potential while avoiding common missteps and discover how to best use AI as a tool for progress rather than a stumbling block. What you'll learn and how you can apply it Apply AI in the right situations and avoid costly mistakes by expecting too much from a developing tech Program macros and scripts with no coding experience using ChatGPT Discover the progress being made with autonomous vehicles and the pitfalls they face This Superstream recording is for you because... You're an ML engineer or developer interested in safely and effectively taking advantage of recent advances in AI while avoiding potential pitfalls. You want to hear about the latest and greatest of AI from experienced industry experts working in the field today. Your organization is quickly advancing into applying AI without a strong map for the potential peaks and valleys ahead. Recommended follow-up: Read Designing Machine Learning Systems (book) Watch Building AI Agents with LLMs (video) Please note that slides or supplemental materials are not available for download from this recording. Resources are only provided at the time of the live event.
    Note: Online resource; title from title details screen (O'Reilly, viewed March 4, 2024)
    URL: lizenzpflichtig
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    Online Resource
    MPI Ethno. Forsch.
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