Practical Machine Learning for Computer Vision:End-to-End Machine Learning for Images


Practical Machine Learning for Computer Vision:End-to-End Machine Learning for Images 1st Edition
by:Valliappa Lakshmanan ,Martin Görner ,Ryan Gillard (Author)
Publisher Finelybook 出版社:O'Reilly Media; 1st edition (August 10,2021)
Language 语言:English
pages 页数:482 pages
ISBN-10 书号:1098102363
ISBN-13 书号:9781098102364

Book 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

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