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Practical Machine Learning for Computer Vision - End-to-End Machine Learning for Images (Paperback)
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Practical Machine Learning for Computer Vision - End-to-End Machine Learning for Images (Paperback)
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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 Goerner, 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
General
Imprint: |
O'Reilly Media
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Country of origin: |
United States |
Release date: |
August 2021 |
Authors: |
Valliappa Lakshmanan
• Martin Goerner
• Ryan Gillard
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Dimensions: |
233 x 178 x 30mm (L x W x T) |
Format: |
Paperback
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Pages: |
350 |
ISBN-13: |
978-1-09-810236-4 |
Categories: |
Books
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LSN: |
1-09-810236-3 |
Barcode: |
9781098102364 |
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