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Application of FPGA to Real-Time Machine Learning

applications. Furthermore, the author draws on his expertise in machine learning and FPGA programming to make progress on a very different problem;

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Real-Time Heterogeneous Video Transcoding for Low-Power Applications

(FPGA) and Application-specific Integrated Circuit (ASIC); * Demonstrates the solution to real problems, with verification through simulation;

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Machine Learning Using R

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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Machine Learning for Time Series Forecasting with Python

treatment of the application of machine learning to time series forecasting. Written for readers who have little to no experience in time;

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Thinking Machines

, explaining how to design through ASIC and FPGA approaches for target machine learning models Surveys current trends and models;

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Conformal Prediction for Reliable Machine Learning

of the framework, demonstrates how to apply it to real-world problems, and presents several adaptations, including active learning, change;

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FPGA-Based Embedded System Developer's Guide

, digital signal processing and top module design * Aims to be a quick reference guide to design digital architecture in the FPGA and develop;

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Machine Learning and Deep Learning in Real-Time Applications

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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Grammar Based Feature Generation for Time Series Prediction

. Application of machine learning techniques to predict time-series continues to attract considerable attention due to the difficulty of the prediction;

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Mastering .NET Machine Learning

, machines. This book is packed with real-world examples to easily use machine learning techniques in your business applications. You will begin;

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Machine Learning Paradigm for Internet of Things Applications

MACHINE LEARNING PARADIGM FOR INTERNET OF THINGS APPLICATIONS As companies globally realize the revolutionary potential of the IoT, they;

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Practical Machine Learning

Book Is For This book has been created for data scientists who want to see machine learning in action and explore its real-world application;

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Industrial Applications of Machine Learning

Industrial Applications of Machine Learning shows how machine learning can be applied to address real-world problems in the fourth;

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Practical Machine Learning for Data Analysis Using Python

of machine learning knowledge to solve different real-world case studies across various fields, including biomedical signal analysis, healthcare;

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Hardware Accelerator Systems for Artificial Intelligence and Machine Learning

accelerator systems for artificial intelligence and machine learning, Introduction to Hardware Accelerator Systems for Artificial Intelligence and;

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Recent Advances in Robot Learning

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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Machine Learning for Developers

Your one-stop guide to becoming a Machine Learning expert. About This Book * Learn to develop efficient and intelligent applications;

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Machine Learning Applications

The publication is attempted to address emerging trends in machine learning applications. Recent trends in information identification have;

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Practical Machine Learning and Image Processing

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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Practical Machine Learning and Image Processing

networks, AdaBoost, XG boost, and convolutional neural networks for image-specific applications. Later yoüll explore how models are made in real;

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Machine Learning with the Elastic Stack

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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Mastering Java Machine Learning

machine learning to real-world data with methodologies, processes, applications, and analysis. * Techniques and experiments developed around the;

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FPGA-based Digital Convolution for Wireless Applications

efficient real-time field-programmable gate array (FPGA) implementations. FPGAs or generic all programmable devices will soon become widespread;

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Cost-Sensitive Machine Learning

efforts and problems in this area. It discusses real-world applications that incorporate the cost of learning into the modeling process;

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Cost-Sensitive Machine Learning

efforts and problems in this area. It discusses real-world applications that incorporate the cost of learning into the modeling process;

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Python Machine Learning Case Studies

hands-on case study-based approach to crack real-world applications to which machine learning concepts can be applied. These smarter machines;

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Mastering Machine Learning with R

Learn * Gain deep insights to learn the applications of machine learning tools to the industry * Manipulate data in R efficiently to prepare;

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