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Learning in Real Time is a concise and practical resource for education professionals teaching live and online or those wanting to humanize;
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have proven to be vital solutions to numerous real-world issues are machine learning and deep learning. These intelligent agents unlock higher;
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Gain time in each day, reduce stress, and improve your classroom learning environment with 35 practical, teacher-proven strategies for;
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Advocates have positioned service-learning as a real-world, real-time opportunity for students to encounter academic knowledge in a;
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Advocates have positioned service-learning as a real-world, real-time opportunity for students to encounter academic knowledge in a;
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of systems through machine learning and deep learning approaches and its implications to the real world Presents data analytics and mining;
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Leverage machine and deep learning models to build applications on real-time data using PySpark. This book is perfect for those who want to;
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Leverage machine and deep learning models to build applications on real-time data using PySpark. This book is perfect for those who want to;
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Since the start of the pandemic, educators all over the world have been learning on the fly how to use the power of digital texts, tools;
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Since the start of the pandemic, educators all over the world have been learning on the fly how to use the power of digital texts, tools;
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Since the start of the pandemic, educators all over the world have been learning on the fly how to use the power of digital texts, tools;
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complex-valued neural networks and derive their learning algorithms to represent these signals at every step of the learning process. This;
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balance of theory and application of machine learning through various real-world use-cases which gives you a comprehensive collection of topics;
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This book lies at the interface of machine learning - a subfield of computer science that develops algorithms for challenging tasks such as;
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incorporates learning in a real-time, noisy domain with teammates and adversaries-a computer-simulated robotic soccer team. Peter Stone's work is the;
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Learning for Time Series Forecasting with Python is full real-world examples, resources and concrete strategies to help readers explore and;
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information out of a large collection of complex educational datasets while learning analytics emphasizes insights and responses to real-time learning;
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The publication is attempted to address emerging trends in machine learning applications. Recent trends in information identification have;
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in-mission real-time learning and optimization.;
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learning system. Since these characteristics are shared by other important real-world application domains, robotics is a highly attractive area for;
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real-life scenarios. After reading this book you will be able to apply image processing techniques and make machine learning models for;
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time and then deployed using various DevOps tools. All the concepts in Practical Machine Learning and Image Processing are explained using real;
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near-real time data with Spark Streaming, how to apply machine learning algorithms with Spark MLlib, how to apply graph algorithms on;
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in the fields of machine learning, big data analytics, signal processing, computational learning theory, and their real-time applications. The;
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This book details the findings of a small-scale research study on the use of real-time coaching in pre-service teacher education, founded;
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