Practical Machine Learning for Computer Vision - by Valliappa Lakshmanan & Martin Görner & Ryan Gillard (Paperback)
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<p/><br></br><p><b> Book Synopsis </b></p></br></br><p>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.</p><p>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.</p><p>You'll learn how to: </p><ul><li>Design ML architecture for computer vision tasks</li><li>Select a model (such as ResNet, SqueezeNet, or EfficientNet) appropriate to your task</li><li>Create an end-to-end ML pipeline to train, evaluate, deploy, and explain your model</li><li>Preprocess images for data augmentation and to support learnability</li><li>Incorporate explainability and responsible AI best practices</li><li>Deploy image models as web services or on edge devices</li><li>Monitor and manage ML models</li></ul><p/><br></br><p><b> About the Author </b></p></br></br><p>Valliappa (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.</p><p>Martin 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.</p><p>Ryan 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.</p>
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