{"product_id":"practical-machine-learning-for-computer-vision-end-to-end-machine-learning-for-images-paperback","title":"Practical Machine Learning for Computer Vision","description":"\u003cp style=\"margin: 0px 0px 14px; padding: 0px; font-family: \" amazon ember arial sans-serif font-size:=\"\"\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 style=\"margin: -4px 0px 14px; padding: 0px; font-family: \" amazon ember arial sans-serif font-size:=\"\"\u003eGoogle 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 style=\"margin: -4px 0px 14px; padding: 0px; font-family: \" amazon ember arial sans-serif font-size:=\"\"\u003eYou'll learn how to:\u003c\/p\u003e\u003cul style=\"margin-top: 0px; margin-right: 0px; margin-left: 20px; padding-right: 0px; padding-left: 0px; font-family: \" amazon ember arial sans-serif font-size:=\"\" margin-bottom:=\"\"\u003e\n\u003cli style=\"margin: 0px 0px 0px 20px; overflow-wrap: break-word;\"\u003eDesign ML architecture for computer vision tasks\u003c\/li\u003e\n\u003cli style=\"margin: 0px 0px 0px 20px; overflow-wrap: break-word;\"\u003eSelect a model (such as ResNet, SqueezeNet, or EfficientNet) appropriate to your task\u003c\/li\u003e\n\u003cli style=\"margin: 0px 0px 0px 20px; overflow-wrap: break-word;\"\u003eCreate an end-to-end ML pipeline to train, evaluate, deploy, and explain your model\u003c\/li\u003e\n\u003cli style=\"margin: 0px 0px 0px 20px; overflow-wrap: break-word;\"\u003ePreprocess images for data augmentation and to support learnability\u003c\/li\u003e\n\u003cli style=\"margin: 0px 0px 0px 20px; overflow-wrap: break-word;\"\u003eIncorporate explainability and responsible AI best practices\u003c\/li\u003e\n\u003cli style=\"margin: 0px 0px 0px 20px; overflow-wrap: break-word;\"\u003eDeploy image models as web services or on edge devices\u003c\/li\u003e\n\u003cli style=\"margin: 0px 0px 0px 20px; overflow-wrap: break-word;\"\u003eMonitor and manage ML models\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp style=\"margin: 0px 0px 0px 20px; overflow-wrap: break-word;\"\u003e \u003c\/p\u003e\u003ch3 style=\"box-sizing: border-box; padding: 0px 0px 4px; margin: 0px; text-rendering: optimizelegibility; font-weight: 700; font-size: 18px; line-height: 24px; color: rgb(15, 17, 17); font-family: \" amazon ember arial sans-serif\u003e   About the Author\u003c\/h3\u003e\u003cdiv class=\"a-section a-spacing-small a-padding-small\" style=\"box-sizing: border-box; margin-bottom: 0px; color: rgb(15, 17, 17); font-family: \" amazon ember arial sans-serif font-size:=\"\" padding:=\"\"\u003e\n\u003cp style=\"box-sizing: border-box; padding: 0px; margin: 0px 0px 14px;\"\u003e\u003cstrong\u003eValliappa (Lak) Lakshmanan\u003c\/strong\u003e 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\n\u003cp style=\"box-sizing: border-box; padding: 0px; margin: 0px 0px 14px;\"\u003e\u003cstrong\u003eMartin Görner\u003c\/strong\u003e 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\n\u003cp style=\"box-sizing: border-box; padding: 0px; margin: 0px;\"\u003e\u003cstrong\u003eRyan Gillard \u003c\/strong\u003eis 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\n\u003c\/div\u003e","brand":"Shroff\/O'Reilly","offers":[{"title":"Default Title","offer_id":50506212573254,"sku":"9789391043834","price":1710.0,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0754\/2797\/1142\/files\/9789391043834_3a6g-nq.jpg?v=1790323314","url":"https:\/\/cb-india.com\/products\/practical-machine-learning-for-computer-vision-end-to-end-machine-learning-for-images-paperback","provider":"Computer Bookshop (India) Pvt Ltd","version":"1.0","type":"link"}