Pulse en una miniatura para ir a Google Books.
Cargando... Practical Machine Learning for Computer Vision: End-to-End Machine Learning for Imagespor Valliappa Lakshmanan
Ninguno Cargando...
Inscríbete en LibraryThing para averiguar si este libro te gustará. Actualmente no hay Conversaciones sobre este libro. Ninguna reseña sin reseñas | añadir una reseña
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 No se han encontrado descripciones de biblioteca. |
Debates activosNinguno
Google Books — Cargando... GénerosSistema Decimal Melvil (DDC)006.31Information Computer Science; Knowledge and Systems Special Topics Artificial Intelligence Machine LearningClasificación de la Biblioteca del CongresoValoraciónPromedio: No hay valoraciones.¿Eres tú?Conviértete en un Autor de LibraryThing. |