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
Print Length 页数: 482 pages
ISBN-10: 1098102363
ISBN-13: 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
