Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
  • 1
    Language: English
    Pages: 1 online resource (1 video file, approximately 3 hr., 14 min.)
    Edition: 1st edition
    Keywords: Electronic videos
    Abstract: Sponsored by intel and LSEG LABS Scaling AI is a notoriously difficult challenge. But it’s easier when you see what’s worked for others—and what hasn’t. This half-day virtual event brings together AI and machine learning engineers from across industries to show how they approach scaling at every stage of the project lifecycle. About the AI Superstream Series: This four-part series of half-day online events is packed with insights from some of the brightest minds in AI. You’ll get a deeper understanding of the latest tools and technologies that can help keep your organization competitive and learn to leverage AI to drive real business results. What you’ll learn and how you can apply it Understand what scaling AI does (and doesn’t) include See what scaling AI might look like from design through deployment Explore what current AI leaders are achieving through scaling Discover real-world technical applications This recording of a live event is for you because… You're a machine learning engineer or data scientist interested in the challenges and benefits of scaling. You’re responsible for scaling your organization's machine learning and are looking for hands-on examples. You're wondering how to improve your own AI and machine learning. Recommended follow-up: Read AI and Analytics at Scale (report) Watch Meet the Expert: Dean Wampler on Scaling ML/AI Applications with Ray (recorded event)
    Note: Online resource; Title from title screen (viewed September 22, 2021) , Mode of access: World Wide Web.
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
  • 2
    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.
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
  • 3
    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
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
Close ⊗
This website uses cookies and the analysis tool Matomo. More information can be found here...