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This book is about making machine learning models and their decisions interpretable. After exploring the concepts of interpretability, you;
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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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This book describes the use of machine learning techniques to build predictive models of uncertainty with application to hydrological;
Vergelijkbare producten zoals Uncertainty Analysis in Rainfall-Runoff Modelling - Application of Machine Learning Techniques
This book describes the use of machine learning techniques to build predictive models of uncertainty with application to hydrological;
Vergelijkbare producten zoals Uncertainty Analysis in Rainfall-Runoff Modelling - Application of Machine Learning Techniques
Work smarter with machine learning! Begin with core machine learning concepts-types of learning, algorithms, data preparation, and more;
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Develop smart applications without spending days and weeks building machine-learning models. With this practical book, you'll learn how to;
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Build machine learning models, natural language processing applications, and recommender systems with PySpark to solve various business;
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Implement machine learning algorithms to build ensemble models using Keras, H2O, Scikit-Learn, Pandas and more Key Features Apply popular;
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Machine learning is an intimidating subject until you know the fundamentals. If you understand basic coding concepts, this introductory;
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Deploy supervised and unsupervised machine learning algorithms using scikit-learn to perform classification, regression, and clustering;
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Design efficient machine learning systems that give you more accurate results About This Book * Gain an understanding of the machine;
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Put machine learning to work in SAP S/4HANA! Get started by reviewing your available tools and implementation options. Then, learn how to;
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Machine learning has taken time to move into the space of academic economics. This is because empirical research in economics;
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Master expert techniques for building automated and highly scalable end-to-end machine learning models and pipelines in Azure using;
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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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This book will help readers understand fundamental and advanced statistical models and deep learning models for robust speaker recognition;
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Predictive Analytics with Microsoft Azure Machine Learning, Second Edition is a practical tutorial introduction to the field of data;
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Implement machine learning models in your iOS applications. This short work begins by reviewing the primary principals of machine learning;
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Prepare to achieve AWS Machine Learning Specialty certification with this complete, up-to-date guide and take the exam with confidence;
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Applied machine learning with a solid foundation in theory. Revised and expanded for TensorFlow 2, GANs, and reinforcement learning;
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Learning services. Designed for experienced IT professionals ready to advance their status, Exam Ref focuses on the critical thinking and decision;
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Thinking Machines: Machine Learning and Its Hardware Implementation covers the theory and application of machine learning, neuromorphic;
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Database developers and administrators will use this book to learn how to deploy machine learning models in Oracle Database and in Oracle's;
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Understand model interpretability methods and apply the most suitable one for your machine learning project. This book details the concepts;
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Explore powerful R packages to create predictive models using ensemble methods Key Features Implement machine learning algorithms to build;
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This book covers the different technologies of Internet, and machine learning capabilities involved in Cognitive Internet of Things (CIoT;
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