Bộ sách luyện thi ETS 2023 LC&RC
199,000₫
299,000₫
Sách gia công, Bìa mềm
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
Thể loại:Computers - Artificial Intelligence (AI)
Năm:2021
In lần thứ:1
Nhà xuát bản:O'Reilly Media
Ngôn ngữ:english
Trang:481
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