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If you're training a machine learning model but aren't sure how to put it into production, this book will get you there. Kubeflow provides;
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production deployments Kubeflow in Action is an authoritative hands-on guide to deploying machine learning to production using the;
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orchestrates workflows by managing machine learning pipelines. You'll learn how to plan and execute a Kubeflow platform that can support workflows from;
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these projects. Understand the steps to build a machine learning pipeline Build your pipeline using components from TensorFlow Extended;
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your machine learning algorithms from the lab to production Understand the threat attackers pose to machine learning solutions;
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Build machine and deep learning systems with the newly released TensorFlow 2 and Keras for the lab, production, and mobile devices Key;
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Build and deploy machine learning and deep learning models in production with end-to-end examples. This book begins with a focus on the;
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learning, this book is for you. If you want to skip the theory and build production-ready machine learning models using Tensorflow without reading;
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from the lab into production, you need confidence that it can stand up to real-world challenges. This book teaches you to design and implement;
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to a survey of some interesting problems, which are good candidates for applying machine and deep learning approaches. The initial chapters;
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to a survey of some interesting problems, which are good candidates for applying machine and deep learning approaches. The initial chapters;
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product in conjunction with another apparel quality textbook. With more than 30 hands-on lab activities and projects to enhance learning, the lab;
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for classification and regression Build, evaluate, and deploy your machine learning solutions to production Who this book is forThis book;
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classification, similarity learning, and more Build, deploy, and scale end-to-end deep neural network models in a production environment Book;
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. With the help of this book, you will be proficient in using TensorFlow, understand deep learning from the basics, and be able to implement;
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This book stems from a unique and a highly effective approach to introducing signal processing, instrumentation, diagnostics, filtering;
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This book stems from a unique and a highly effective approach to introducing signal processing, instrumentation, diagnostics, filtering;
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with building and deploying robust machine learning solutions. As you advance, you'll explore how to create your own toolsets for training and;
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as well testing, shale reservoirs and production optimization. Petroleum engineers are quickly applying machine learning techniques to their;
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Create and manage Microsoft's tool environments for development, testing, and production of a machine learning project Implement and deploy;
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machine learning solution Create and manage Microsoft's tool environments for development, testing, and production of a machine learning;
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Learn how to use TensorFlow 2.0 to build machine learning and deep learning models with complete examples. The book begins with;
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Learn how to use TensorFlow 2.0 to build machine learning and deep learning models with complete examples. The book begins with introducing;
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including TensowFlow and CNTK to give you a broader perspective of the deep learning ecosystem. What You Will Learn Build production-ready solutions;
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Explore machine learning workflows for stating ML problems in a concise and clear manner using MLflow Use MLflow to iteratively develop a ML;
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proactive alerting Train and deploy supervised machine learning models for real-time inference Discover various tips and tricks to get the most;
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-latency-accuracy trade-offs. From first principles to lab prototypes, this book provides a comprehensive view of this emerging topic for both the;
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