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    Détails du Torrent Pour "Practical Machine Learning for Computer Vision - (BookRAR)"

    Practical Machine Learning for Computer Vision - (BookRAR)

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    Dernière vérification: 22-11-2021 02:43:00

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    _NAME_:Practical Machine Learning for Computer Vision - (BookRAR)
    Description:

    Description

    This practical book shows you how to employ machine learning models to extract information from images. ML engineers and data scientists will learn how to solve a variety of image problems including classification, object detection, autoencoders, image generation, counting, and captioning with proven ML techniques. This book provides a great introduction to end-to-end deep learning: dataset creation, data preprocessing, model design, model training, evaluation, deployment, and interpretability.

    Google engineers Valliappa Lakshmanan, Martin Görner, and Ryan Gillard show you how to develop accurate and explainable computer vision ML models and put them into large-scale production using robust ML architecture in a flexible and maintainable way. You’ll learn how to design, train, evaluate, and predict with models written in TensorFlow or Keras.

    You’ll learn how to:

       Design ML architecture for computer vision tasks
       Select a model (such as ResNet, SqueezeNet, or EfficientNet) appropriate to your task
       Create an end-to-end ML pipeline to train, evaluate, deploy, and explain your model
       Preprocess images for data augmentation and to support learnability
       Incorporate explainability and responsible AI best practices
       Deploy image models as web services or on edge devices
       Monitor and manage ML models

    Book Details

       Language: English
       Published: 2021
       ISBN: 1098102363
       Format: True PDF
    YouTube Video:
    Catégorie:Books
    Langue :English  English
    Taille totale:56.15 MB
    Info Hash:DE37BD9D5FEA4B6EC877A08F407348D7F9CAD080
    Ajouté par:bookrar Verified UploaderBook Worm
    Date:2021-08-28 11:06:42
    Statut Torrent:Torrent Verified


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