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  • 1
    Online-Ressource
    Online-Ressource
    Konpyūta bijon no tame no jissen kikai gakushū : moderu ākitekucha kara MLOps made = Practical machine learning for computer vision : end-to-end machine learning for images (2023)
    Tōkyō-to Shinjuku-ku : Orairī Japan
    Details
    Orig.schr. Ausgabe: 初版.
    Titel: コンピュータビジョンのための実践機械学習 : : モデルアーキテクチャからMLOpsまで = Practical machine learning for computer vision : end-to-end machine learning for images /
    Verlag: オライリー・ジャパン,
    ISBN: 9784814400386 , 4814400381
    Sprache: Japanisch
    Seiten: 1 online resource (520 pages) , illustrations.
    Ausgabe: Shohan.
    Originaltitel: Practical machine learning for computer vision
    DDC: 006.37
    Schlagwort(e): Computer vision ; Machine learning ; Vision par ordinateur ; Apprentissage automatique
    Anmerkung: In Japanese.
    URL: lizenzpflichtig
    Bibliothek Standort Signatur Band/Heft/Jahr Verfügbarkeit
    BibTip Andere fanden auch interessant ...
    Online-Ressource
    MPI Ethno. Forsch.
  • 2
    Online-Ressource
    Online-Ressource
    Python de hajimeru ōpun endo na shinkateki arugorizumu : hassangata no kikai gakushū ni yoru tayō na kai no tansaku (2023)
    Tōkyō-to Shinjuku-ku : Orairī Japan
    Details
    Orig.schr. Ausgabe: 初版.
    Titel: Pythonではじめるオープンエンドな進化的アルゴリズム : : 発散型の機械学習による多様な解の探索 /
    Verlag: 東京都新宿区 : オライリー・ジャパン
    ISBN: 9784814400003 , 4814400004
    Sprache: Japanisch
    Seiten: 1 online resource (296 pages)
    Ausgabe: Shohan.
    DDC: 005.1
    Schlagwort(e): Computer algorithms ; Machine learning ; Python (Computer program language) ; Algorithmes ; Apprentissage automatique ; Python (Langage de programmation) ; algorithms
    Anmerkung: Includes bibiographical references
    URL: lizenzpflichtig
    Bibliothek Standort Signatur Band/Heft/Jahr Verfügbarkeit
    BibTip Andere fanden auch interessant ...
    Online-Ressource
    MPI Ethno. Forsch.
  • 3
    Online-Ressource
    Online-Ressource
    Kikai gakushū shisutemu dezain : jitsūn'yō reberu no apurikēshon o jitsugensuru keizokuteki hanpuku purosesu (2023)
    Tōkyō-to Shinjuku-ku : Orairī Japan
    Details
    Orig.schr. Ausgabe: 初版.
    Titel: 機械学習システムデザイン : : 実運用レベルのアプリケーションを実現する継続的反復プロセス /
    Verlag: オライリー・ジャパン,
    ISBN: 9784814400409 , 4814400403
    Sprache: Japanisch
    Seiten: 1 online resource (408 pages)
    Ausgabe: Shohan.
    Originaltitel: Designing machine learning systems
    DDC: 006.3/1
    Schlagwort(e): Machine learning ; Artificial intelligence Industrial applications ; System design ; Artificial intelligence Design ; Computational learning theory ; Engineering Data processing ; Apprentissage automatique ; Intelligence artificielle ; Applications industrielles ; Conception de systèmes ; Théorie de l'apprentissage informatique ; Ingénierie ; Informatique
    Kurzfassung: "Machine learning systems are both complex and unique. Complex because they consist of many different components and involve many different stakeholders. Unique because they're data dependent, with data varying wildly from one use case to the next. In this book, you'll learn a holistic approach to designing ML systems that are reliable, scalable, maintainable, and adaptive to changing environments and business requirements. Author Chip Huyen, co-founder of Claypot AI, considers each design decision--such as how to process and create training data, which features to use, how often to retrain models, and what to monitor--in the context of how it can help your system as a whole achieve its objectives. The iterative framework in this book uses actual case studies backed by ample references".
    Anmerkung: In Japanese.
    URL: lizenzpflichtig
    Bibliothek Standort Signatur Band/Heft/Jahr Verfügbarkeit
    BibTip Andere fanden auch interessant ...
    Online-Ressource
    MPI Ethno. Forsch.
  • 4
    Online-Ressource
    Online-Ressource
    Kikai gakushū ni yoru jitsuyō apurikēshon kōchiku : jirei o tsūjite manabu, sekkei kara honban kadō made no purosesu (2021)
    Tōkyō-to Shinjuku-ku : Orairī Japan
    Details
    Orig.schr. Ausgabe: 初版.
    Titel: 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 /
    Verlag: オライリー・ジャパン,
    ISBN: 9784873119502 , 4873119502
    Sprache: Japanisch
    Seiten: 1 online resource (256 pages)
    Ausgabe: Shohan.
    Originaltitel: Building machine learning powered applications
    DDC: 006.31
    Schlagwort(e): Machine learning ; Application software Development ; Apprentissage automatique ; Logiciels d'application ; Développement ; Application software ; Development ; Machine learning ; Electronic books
    Kurzfassung: "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." --
    Anmerkung: Online resource; title from title details screen (O'Reilly, viewed April 19, 2022)
    URL: lizenzpflichtig
    Bibliothek Standort Signatur Band/Heft/Jahr Verfügbarkeit
    BibTip Andere fanden auch interessant ...
    Online-Ressource
    MPI Ethno. Forsch.
  • 5
    Online-Ressource
    Online-Ressource
    Scikit-learn, Keras, TensorFlow ni yoru jissen kikai gakushū (2020)
    Tōkyō-to Shinjuku-ku : Orairī Japan
    Details
    Orig.schr. Ausgabe: 第 2版.
    Titel: Scikit-learn, Keras, TensorFlowによる実践機械学習 /
    Verlag: オライリー・ジャパン,
    ISBN: 9784873119281 , 4873119286
    Sprache: Japanisch
    Seiten: 1 online resource (832 pages)
    Ausgabe: Dai 2-han.
    Originaltitel: Hands-on machine learning with Scikit-Learn, Keras, and TensorFlow
    Paralleltitel: Parallele Sprachausgabe Saikittorān to tensorufurō ni yoru jissen kikai gakushū.
    DDC: 006.3/1
    Schlagwort(e): TensorFlow ; Machine learning ; Artificial intelligence ; Python (Computer program language) ; Artificial Intelligence ; Apprentissage automatique ; Intelligence artificielle ; Python (Langage de programmation) ; artificial intelligence ; Artificial intelligence ; Machine learning ; Python (Computer program language) ; Electronic books
    Kurzfassung: "Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how. By using concrete examples, minimal theory, and two production-ready Python frameworks - Scikit-Learn and TensorFlow 2 - the author helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You'll learn a range of techniques, starting with simple linear regression and progressing to deep neural networks. With exercises in each chapter to help you apply what you've learned, all you need is programming experience to get started." --
    Anmerkung: Online resource; title from title details screen (O’Reilly, viewed April 20, 2022)
    URL: lizenzpflichtig
    Bibliothek Standort Signatur Band/Heft/Jahr Verfügbarkeit
    BibTip Andere fanden auch interessant ...
    Online-Ressource
    MPI Ethno. Forsch.
  • 6
    Online-Ressource
    Online-Ressource
    Python de hajimeru kyōshi nashi gakushū : kikai gakushū no kanōsei o hirogeru raberu nashi dēta no riyō (2020)
    Tōkyō-to Shinjuku-ku : Orairī Japan
    Details
    Orig.schr. Ausgabe: 初版.
    Titel: Pythonではじめる教師なし学習 : : 機械学習の可能性を広げるラベルなしデータの利用 /
    Verlag: オライリー・ジャパン,
    ISBN: 9784873119106 , 4873119103
    Sprache: Japanisch
    Seiten: 1 online resource (344 pages)
    Ausgabe: Shohan.
    Originaltitel: Hands-on unsupervised learning using Python
    DDC: 006.31
    Schlagwort(e): Machine learning ; Artificial intelligence ; Python (Computer program language) ; Artificial Intelligence ; Apprentissage automatique ; Intelligence artificielle ; Python (Langage de programmation) ; artificial intelligence ; Artificial intelligence ; Machine learning ; Python (Computer program language) ; Electronic books
    Kurzfassung: Many industry experts consider unsupervised learning the next frontier in artificial intelligence, one that may hold the key to the holy grail in AI research, the so-called general artificial intelligence. Since the majority of the world's data is unlabeled, conventional supervised learning cannot be applied; this is where unsupervised learning comes in. Unsupervised learning can be applied to unlabeled datasets to discover meaningful patterns buried deep in the data, patterns that may be near impossible for humans to uncover. Author Ankur Patel provides practical knowledge on how to apply unsupervised learning using two simple, production-ready Python frameworks - scikit-learn and TensorFlow using Keras. With the hands-on examples and code provided, you will identify difficult-to-find patterns in data and gain deeper business insight, detect anomalies, perform automatic feature engineering and selection, and generate synthetic datasets. All you need is programming and some machine learning experience to get started.
    Anmerkung: Includes bibiographical references and index. - Online resource; title from title details screen (O'Reilly, viewed April 20, 2022)
    URL: lizenzpflichtig
    Bibliothek Standort Signatur Band/Heft/Jahr Verfügbarkeit
    BibTip Andere fanden auch interessant ...
    Online-Ressource
    MPI Ethno. Forsch.
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