{"product_id":"practical-machine-learning-for-computer-vision-end-to-end-machine-learning-for-images-9781098102364","title":"Practical Machine Learning for Computer Vision: End-To-End Machine Learning for Images","description":"\u003cp\u003eThis 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. \u003c\/p\u003e\u003cp\u003e 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. \u003c\/p\u003e\u003cp\u003e You'll learn how to: \u003c\/p\u003e\u003cul\u003e \u003cli\u003eDesign ML architecture for computer vision tasks \u003c\/li\u003e\n\u003cli\u003eSelect a model (such as ResNet, SqueezeNet, or EfficientNet) appropriate to your task \u003c\/li\u003e\n\u003cli\u003eCreate an end-to-end ML pipeline to train, evaluate, deploy, and explain your model \u003c\/li\u003e\n\u003cli\u003ePreprocess images for data augmentation and to support learnability \u003c\/li\u003e\n\u003cli\u003eIncorporate explainability and responsible AI best practices \u003c\/li\u003e\n\u003cli\u003eDeploy image models as web services or on edge devices \u003c\/li\u003e\n\u003cli\u003eMonitor and manage ML models \u003c\/li\u003e\n\u003c\/ul\u003e\u003cbr\u003e\u003cbr\u003e\u003cbr\u003e\u003cb\u003eAbout the Author\u003c\/b\u003e\u003cbr\u003e\u003cp\u003eValliappa (Lak) Lakshmanan is the director of analytics and AI solutions at Google Cloud, where he leads a team building cross-industry solutions to business problems. His mission is to democratize machine learning so that it can be done by anyone anywhere.\u003c\/p\u003e\u003cp\u003eMartin Görner is a product manager for Keras\/TensorFlow focused on improving the developer experience when using state-of-the-art models. He's passionate about science, technology, coding, algorithms, and everything in between.\u003c\/p\u003e\u003cp\u003eRyan Gillard is an AI engineer in Google Cloud's Professional Services organization, where he builds ML models for a wide variety of industries. He started his career as a research scientist in the hospital and healthcare industry. With degrees in neuroscience and physics, he loves working at the intersection of those disciplines exploring intelligence through mathematics.\u003c\/p\u003e\u003cbr\u003e","brand":"O'Reilly Media","offers":[{"title":"Default Title","offer_id":50525634855186,"sku":"9781098102364","price":64.99,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0831\/4771\/8930\/files\/img_c23a7870-a181-4483-acda-89eff48c557e.jpg?v=1731229478","url":"https:\/\/surprise-castle.myshopify.com\/products\/practical-machine-learning-for-computer-vision-end-to-end-machine-learning-for-images-9781098102364","provider":"Surprise Castle","version":"1.0","type":"link"}