Explainable Machine Learning Models and Architectures

Suman Lata Tripathi, Mufti Mahmud

• Publisher: Wiley-Scrivener
• Year: 2023
• Print ISBN: 9781394185849
• eBook ISBN: 9781394186556
• Edition: 1
• Topic: Computer Science
• Subtopic: Artificial Intelligence (AI) & Semantics
• Index: Computer Science

EXPLAINABLE MACHINE LEARNING MODELS AND ARCHITECTURES

This cutting-edge new volume covers the hardware architecture implementation, the software implementation approach, and the efficient hardware of machine learning applications.

Machine learning and deep learning modules are now an integral part of many smart and automated systems where signal processing is performed at different levels. Signal processing in the form of text, images, or video needs large data computational operations at the desired data rate and accuracy. Large data requires more use of integrated circuit (IC) area with embedded bulk memories that further lead to more IC area. Trade-offs between power consumption, delay and IC area are always a concern of designers and researchers. New hardware architectures and accelerators are needed to explore and experiment with efficient machine-learning models. Many real-time applications like the processing of biomedical data in healthcare, smart transportation, satellite image analysis, and IoT-enabled systems have a lot of scope for improvements in terms of accuracy, speed, computational powers, and overall power consumption.

This book deals with the efficient machine and deep learning models that support high-speed processors with reconfigurable architectures like graphic processing units (GPUs) and field programmable gate arrays (FPGAs), or any hybrid system. Whether for the veteran engineer or scientist working in the field or laboratory, or the student or academic, this is a must-have for any library.

Table of contents

• Cover
• Table of Contents
• Series Page
• Title Page
• Copyright Page
• Preface
• Acknowledgements
• 1 A Comprehensive Review of Various Machine Learning Techniques
• 2 Artificial Intelligence and Image Recognition Algorithms
• 3 Efficient Architectures and Trade-Offs for FPGA-Based Real-Time Systems
• 4 A Low-Power Audio Processing Using Machine Learning Module on FPGA and Applications
• 5 Synthesis and Time Analysis of FPGA-Based DIT-FFT Module for Efficient VLSI Signal Processing Applications
• 6 Artificial Intelligence–Based Active Virtual Voice Assistant
• 7 Image Forgery Detection: An Approach with Machine Learning
• 8 Applications of Artificial Neural Networks in Optical Performance Monitoring
• 9 Website Development with Django Web Framework
• 10 Revenue Forecasting Using Machine Learning Models
• 11 Application of Machine Learning Optimization Techniques in Wind Resource Assessment
• 12 IoT to Scale-Up Smart Infrastructure in Indian Cities: A New Paradigm
• Index
• Also of Interest
• End User License Agreement