Machine Learning Governance For Managers
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Machine Learning Governance For Managers
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Author : Francesca Lazzeri
language : en
Publisher: Springer Nature
Release Date : 2023-11-24
Machine Learning Governance For Managers written by Francesca Lazzeri and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-24 with Mathematics categories.
Machine Learning Governance for Managers provides readers with the knowledge to unlock insights from data and leverage AI solutions. In today's business landscape, most organizations face challenges in scaling and maintaining a sustainable machine learning model lifecycle. This book offers a comprehensive framework that covers business requirements, data generation and acquisition, modeling, model deployment, performance measurement, and management, providing a range of methodologies, technologies, and resources to assist data science managers in adopting data and AI-driven practices. Particular emphasis is given to ramping up a solution quickly, detailing skills and techniques to ensure the right things are measured and acted upon for reliable results and high performance. Readers will learn sustainable tools for implementing machine learning with existing IT and privacy policies, including versioning all models, creating documentation, monitoring models and their results, and assessing their causal business impact. By overcoming these challenges, bottom-line gains from AI investments can be realized. Organizations that implement all aspects of AI/ML model governance can achieve a high level of control and visibility over how models perform in production, leading to improved operational efficiency and a higher ROI on AI investments. Machine Learning Governance for Managers helps to effectively control model inputs and understand all the variables that may impact your results. Don't let challenges in machine learning hinder your organization's growth - unlock its potential with this essential guide.
Artificial Intelligence And Machine Learning In Management Science Emerging Research And Applications
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Author : Ms. Meenu Shukla
language : en
Publisher: NC Publishers
Release Date : 2025-07-01
Artificial Intelligence And Machine Learning In Management Science Emerging Research And Applications written by Ms. Meenu Shukla and has been published by NC Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-01 with Antiques & Collectibles categories.
As the global business environment continues to evolve, artificial intelligence (AI) and machine learning (ML) have emerged as powerful tools for enhancing decision-making, optimizing operations, and fostering innovation across various sectors. This book brings together a collection of scholarly contributions from researchers and practitioners who are at the forefront of integrating these technologies with managerial practices. The chapters offer both theoretical insights and practical applications, covering domains such as operations research, strategic planning, supply chain optimization, marketing analytics, financial forecasting, and human resource management.
Machine Learning In Finance Risk Management Trading And Fraud Detection
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Author : Dr. Aman Gupta
language : en
Publisher: Xoffencerpublication
Release Date : 2023-07-04
Machine Learning In Finance Risk Management Trading And Fraud Detection written by Dr. Aman Gupta and has been published by Xoffencerpublication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-07-04 with Computers categories.
Artificial intelligence (AI) systems are machine-based systems with varying degrees of autonomy that generate predictions, suggestions, or judgements for a set of humanspecified goals utilizing enormous numbers of alternative data sources and data analytics referred to as "big data"3 (OECD, 2019). Artificial intelligence (AI) systems are sometimes referred to as intelligent machines. Systems that are powered by artificial intelligence (AI) are increasingly finding applications in a wide range of fields, including the medical field, the financial sector, and the armed forces. Common synonyms for artificial intelligence (AI) include "machine learning" and "machine learning systems." An explanation of artificial intelligence may be found in the following: "Artificial intelligence systems" are defined by the Oxford English Dictionary as "machine-based systems that can exhibit varying degrees of autonomy." You may learn more about this concept by reading the page titled "Artificial Intelligence Systems." Once they have access to the data, the models have the potential to "self-improve" by inferentially learning from further data sets without the need for human instruction. This may occur if they learn to draw conclusions from other data sets via inference. The acceleration and strengthening of a tendency toward digitalization that was already apparent before the pandemic is a direct outcome of the spread of the COVID-19 virus. This trend was already clear before the epidemic. Utilization of artificial intelligence is included in this trend. The abundance of data that is already available, in addition to the advancements in computer capacity that have made computers both more affordable and more powerful, have made it possible for artificial intelligence to play an increasingly important role in the financial sector. This role can be seen in asset management, algorithmic trading, credit underwriting, and blockchain-based financial services, among other applications. AI4 is integrated into goods and services across a wide range of sectors, including healthcare, autos, consumer items, and the phrase "internet of things" is abbreviated as "IoT."
Ecmlg 2022 18th European Conference On Management Leadership And Governance
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Author : Florinda Matos
language : en
Publisher: Academic Conferences and publishing limited
Release Date : 2022-11-10
Ecmlg 2022 18th European Conference On Management Leadership And Governance written by Florinda Matos and has been published by Academic Conferences and publishing limited this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-11-10 with Business & Economics categories.
Practical And Advanced Machine Learning Methods For Model Risk Management
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Author : INDRA REDDY MALLELA NAGARJUNA PUTTA PROF.(DR.) AVNEESH KUMAR
language : en
Publisher: DeepMisti Publication
Release Date : 2024-12-22
Practical And Advanced Machine Learning Methods For Model Risk Management written by INDRA REDDY MALLELA NAGARJUNA PUTTA PROF.(DR.) AVNEESH KUMAR and has been published by DeepMisti Publication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-22 with Computers categories.
In today’s fast-evolving landscape of artificial intelligence (AI) and machine learning (ML), organizations are increasingly relying on advanced models to drive decision-making and innovation across various sectors. As machine learning technologies grow in complexity and scale, managing the risks associated with these models becomes a critical concern. From biases in algorithms to the interpretability of predictions, the potential for errors and unintended consequences demands rigorous frameworks for assessing and mitigating risks. "Practical and Advanced Machine Learning Methods for Model Risk Management" explores these challenges in depth. It is designed to provide both foundational knowledge and advanced techniques for effectively managing model risks throughout their lifecycle—from development and deployment to monitoring and updating. This book caters to professionals working in data science, machine learning engineering, risk management, and governance, offering a comprehensive understanding of how to balance model performance with robust risk management practices. The book begins with a strong foundation in the principles of model risk management (MRM), exploring the core concepts of risk identification, assessment, and mitigation. From there, it dives into more advanced techniques for managing risks in complex ML models, including methods for ensuring model fairness, transparency, and interpretability, as well as strategies for dealing with adversarial attacks, data security concerns, and ethical considerations. Throughout, we emphasize the importance of collaboration between data scientists, risk professionals, and organizational leaders in creating a culture of responsible AI. This collaborative approach is crucial for building models that not only perform at the highest levels but also adhere to ethical standards and regulatory requirements. By the end of this book, readers will have a deep understanding of the critical role that risk management plays in AI and machine learning, as well as the practical tools and methods needed to implement a comprehensive MRM strategy. Whether you are just beginning your journey in model risk management or are seeking to refine your existing processes, this book serves as an essential resource for navigating the complexities of machine learning in today’s rapidly changing technological landscape. We hope this book equips you with the knowledge to effectively address the risks of ML models and apply these insights to improve both the performance and trustworthiness of your AI systems. Thank you for embarking on this journey with us. Authors
Machine Intelligence And Signal Processing
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Author : Sonali Agarwal
language : en
Publisher: Springer Nature
Release Date : 2020-02-25
Machine Intelligence And Signal Processing written by Sonali Agarwal and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-02-25 with Technology & Engineering categories.
This book features selected high-quality research papers presented at the International Conference on Machine Intelligence and Signal Processing (MISP 2019), held at the Indian Institute of Technology, Allahabad, India, on September 7–10, 2019. The book covers the latest advances in the fields of machine learning, big data analytics, signal processing, computational learning theory, and their real-time applications. The topics covered include support vector machines (SVM) and variants like least-squares SVM (LS-SVM) and twin SVM (TWSVM), extreme learning machine (ELM), artificial neural network (ANN), and other areas in machine learning. Further, it discusses the real-time challenges involved in processing big data and adapting the algorithms dynamically to improve the computational efficiency. Lastly, it describes recent developments in processing signals, for instance, signals generated from IoT devices, smart systems, speech, and videos and addresses biomedical signal processing: electrocardiogram (ECG) and electroencephalogram (EEG).
Artificial Intelligence Enabled Management
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Author : Rubee Singh
language : en
Publisher: Walter de Gruyter GmbH & Co KG
Release Date : 2024-06-04
Artificial Intelligence Enabled Management written by Rubee Singh and has been published by Walter de Gruyter GmbH & Co KG this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-06-04 with Business & Economics categories.
Companies in developing countries are adopting Artificial Intelligence applications to increase efficiency and open new markets for their products. This book explores the multifarious capabilities and applications of AI in the context of these emerging economies and its role as a driver for decision making in current management practices. Artificial Intelligence Enabled Management argues that the economic problems facing academics, professionals, managers, governments, businesses and those at the bottom of the economic pyramid have a technical solution that relates to AI. Businesses in developing countries are using cutting-edge AI-based solutions to improve autonomous delivery of goods and services, implement automation of production and develop mobile apps for services and access to credit. By integrating data from websites, social media and conventional channels, companies are developing data management platforms, good business plans and creative business models. By increasing productivity, automating business processes, financial solutions and government services, AI can drive economic growth in these emerging economies. Public and private sectors can work together to find innovative solutions that simultaneously alleviate poverty and inequality and increase economic mobility and prosperity. The thought-provoking contributions in this book also bring attention to new barriers that have emerged in the acceptance, use, integration and deployment of AI by businesses in developing countries and explore the often-overlooked drawbacks of AI adoption that can hinder or even cause value loss. The book is a must-read for policymakers, researchers, and anyone interested in understanding the critical role of AI in the emerging economy perspective.
Proceedings Of The 2023 3rd International Conference On Public Management And Intelligent Society Pmis 2023
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Author : Nadeem Akhtar
language : en
Publisher: Springer Nature
Release Date : 2023-07-25
Proceedings Of The 2023 3rd International Conference On Public Management And Intelligent Society Pmis 2023 written by Nadeem Akhtar and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-07-25 with Computers categories.
This is an open access book.The 3rd International Conference on Public Management and Intelligent Society(PMIS 2023) will be held on March 10-12, 2023 in Shanghai, China. PMIS 2021 and PMIS 2022 have been successfully held in the last 2 years, providing an academic exchange platform for participants from all over the world. The conference discussed the latest topics in the field of public management and intelligent society, and the wonderful presentations were given by invited distinguished speakers and praised by scholars. Building an intelligent society and studying public management have always been a leading and hot issue. PMIS 2023 will focus on public management in an intelligent society, technological innovation in an intelligent society and advanced intelligent transportation system to discuss further. The aim of PMIS 2023 is to bring together innovative academics and industrial experts in the field of Public Management and Intelligent Society to a common forum. The primary goal to promote research and developmental activities and another goal is to promote scientific information interchange between researchers, developers, students, and practitioners in related fields.
Utilization Of Ai Technology In Supply Chain Management
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Author : Pandey, Digvijay
language : en
Publisher: IGI Global
Release Date : 2024-03-01
Utilization Of Ai Technology In Supply Chain Management written by Pandey, Digvijay and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-03-01 with Business & Economics categories.
The surge in digital transformation and the integration of innovative technologies into manufacturing processes have given rise to a pressing issue in supply chain management. Businesses are in dire need of solutions to navigate this complexity and harness the true potential of intelligent supply chains. Utilization of AI Technology in Supply Chain Management is a comprehensive guide tailored for academic scholars seeking to unravel the mysteries of artificial intelligence (AI) and machine learning (ML) in the context of supply chain management. Amid the hype surrounding AI and ML, there exists a critical need to bridge the gap between human expertise and technological advancements. Utilization of AI Technology in Supply Chain Management addresses this necessity by delving into real-world instances where teams have successfully employed these innovative technologies to enhance supply chain performance, reduce inventory, and optimize routes. The adoption of AI and ML is not just a trend; it is the cornerstone of digital acceleration initiatives, making it imperative for scholars to understand and leverage these technologies effectively.
Machine Learning For Financial Risk Management With Python
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Author : Abdullah Karasan
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2021-12-07
Machine Learning For Financial Risk Management With Python written by Abdullah Karasan and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-12-07 with Computers categories.
Financial risk management is quickly evolving with the help of artificial intelligence. With this practical book, developers, programmers, engineers, financial analysts, risk analysts, and quantitative and algorithmic analysts will examine Python-based machine learning and deep learning models for assessing financial risk. Building hands-on AI-based financial modeling skills, you'll learn how to replace traditional financial risk models with ML models. Author Abdullah Karasan helps you explore the theory behind financial risk modeling before diving into practical ways of employing ML models in modeling financial risk using Python. With this book, you will: Review classical time series applications and compare them with deep learning models Explore volatility modeling to measure degrees of risk, using support vector regression, neural networks, and deep learning Improve market risk models (VaR and ES) using ML techniques and including liquidity dimension Develop a credit risk analysis using clustering and Bayesian approaches Capture different aspects of liquidity risk with a Gaussian mixture model and Copula model Use machine learning models for fraud detection Predict stock price crash and identify its determinants using machine learning models