{"product_id":"practical-machine-learning-for-computer-vision","title":"Practical Machine Learning for Computer Vision","description":"margin: 0px 0px 14px; padding: 0px; font-family: \"Amazon Ember\", Arial, sans-serif; font-size: 14px;'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.'margin: -4px 0px 14px; padding: 0px; font-family: \"Amazon Ember\", Arial, sans-serif; font-size: 14px;'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.'margin: -4px 0px 14px; padding: 0px; font-family: \"Amazon Ember\", Arial, sans-serif; font-size: 14px;'You'll learn how to:\u003cul style=\"\" ember arial sans-serif ml architecture for computer vision tasks a model as resnet squeezenet or efficientnet appropriate to your task an end-to-end pipeline train evaluate deploy and explain images data augmentation support learnability explainability responsible ai best practices image models web services on edge devices manage break-word border-box optimizelegibility rgb the authorclass a-spacing-small a-padding-small lakshmanan is director of analytics solutions at google cloud where he leads team building cross-industry business problems. his mission democratize machine learning so that it can be done anyone anywhere. g product manager keras focused improving developer experience when using state-of-the-art models. passionate about science technology coding algorithms everything in between. gillard engineer professional organization builds wide variety industries. started career research scientist hospital healthcare industry. with degrees neuroscience physics loves working intersection those disciplines exploring intelligence through mathematics. margin-right:=\"\" margin-left:=\"\" padding-right:=\"\" padding-left:=\"\" font-family:=\"\" font-size:=\"\" margin-bottom:=\"\" overflow-wrap:=\"\" padding:=\"\" margin:=\"\" text-rendering:=\"\" font-weight:=\"\" line-height:=\"\" color:=\"\"\u003e\u003c\/ul\u003e","brand":"BOOKZONE","offers":[{"title":"Default Title","offer_id":43097494978639,"sku":"9789391043834","price":1615.0,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0635\/9583\/9567\/files\/Practical-Machine-Learning-for-Computer-Vision-32033827061839.jpg?v=1767505222","url":"https:\/\/bookzoneindia.com\/products\/practical-machine-learning-for-computer-vision","provider":"BOOKZONE","version":"1.0","type":"link"}