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  • MPI Ethno. Forsch.  (2)
  • Japanese  (2)
  • Polish
  • Kikuchi, Akira  (2)
  • Machine learning  (2)
  • 1
    Orig.schr. Ausgabe: 初版.
    Title: 動かして学ぶAI・機械学習の基礎 : : TensorFlowによるコンピュータビジョン, 自然言語処理, 時系列データの予測とデプロイ /
    Publisher: オライリー・ジャパン,
    ISBN: 9784873119809 , 4873119804
    Language: Japanese
    Pages: 1 online resource (384 pages)
    Edition: Shohan.
    Uniform Title: AI and machine learning for coders
    DDC: 006.3/1
    Keywords: Machine learning ; Artificial intelligence
    Note: In Japanese.
    Library Location Call Number Volume/Issue/Year Availability
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  • 2
    Orig.schr. Ausgabe: 初版.
    Title: 機械学習による実用アプリケーション構築 : : 事例を通じて学ぶ, 設計から本番稼働までのプロセス /
    Publisher: オライリー・ジャパン,
    ISBN: 9784873119502 , 4873119502
    Language: Japanese
    Pages: 1 online resource (256 pages)
    Edition: Shohan.
    Uniform Title: Building machine learning powered applications
    DDC: 006.31
    Keywords: Machine learning ; Application software Development ; Apprentissage automatique ; Logiciels d'application ; Développement ; Application software ; Development ; Machine learning ; Electronic books
    Abstract: "Learn the skills necessary to design, build, and deploy applications powered by machine learning (ML). Through the course of this hands-on book, you'll build an example ML-driven application from initial idea to deployed product. Data scientists, software engineers, and product managers--including experienced practitioners and novices alike--will learn the tools, best practices, and challenges involved in building a real-world ML application step by step. Author Emmanuel Ameisen, an experienced data scientist who led an AI education program, demonstrates practical ML concepts using code snippets, illustrations, screenshots, and interviews with industry leaders. Part I teaches you how to plan an ML application and measure success. Part II explains how to build a working ML model. Part III demonstrates ways to improve the model until it fulfills your original vision. Part IV covers deployment and monitoring strategies. This book will help you:Define your product goal and set up a machine learning problemBuild your first end-to-end pipeline quickly and acquire an initial datasetTrain and evaluate your ML models and address performance bottlenecksDeploy and monitor your models in a production environment." --
    Note: Online resource; title from title details screen (O'Reilly, viewed April 19, 2022)
    Library Location Call Number Volume/Issue/Year Availability
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