Machine Learning And Data Sciences For Financial Markets
DOWNLOAD
Download Machine Learning And Data Sciences For Financial Markets PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Machine Learning And Data Sciences For Financial Markets book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
Machine Learning And Data Sciences For Financial Markets
DOWNLOAD
Author : Agostino Capponi
language : en
Publisher: Cambridge University Press
Release Date : 2023-06
Machine Learning And Data Sciences For Financial Markets written by Agostino Capponi and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-06 with Business & Economics categories.
Learn how cutting-edge AI and data science techniques are integrated in financial markets from leading experts in the industry.
Machine Learning And Modeling Techniques In Financial Data Science
DOWNLOAD
Author : Chen, Haojun
language : en
Publisher: IGI Global
Release Date : 2025-01-22
Machine Learning And Modeling Techniques In Financial Data Science written by Chen, Haojun and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-22 with Business & Economics categories.
The integration of machine learning and modeling in finance is transforming how data is analyzed, enabling more accurate predictions, risk assessments, and strategic planning. These advanced techniques empower financial professionals to uncover hidden patterns, automate complex processes, and enhance decision-making in volatile markets. As industries increasingly rely on data-driven insights, the adoption of these tools contributes to greater efficiency, reduced uncertainty, and competitive advantage. This technological shift not only drives innovation within financial sectors but also supports broader economic stability and growth by improving forecasting and mitigating risks. Machine Learning and Modeling Techniques in Financial Data Science provides an updated review and highlights recent theoretical advances and breakthroughs in professional practices within financial data science, exploring the strategic roles of machine learning and modeling techniques across various domains in finance. It offers a comprehensive collection that brings together a wealth of knowledge and experience. Covering topics such as algorithmic trading, financial technology (FinTech), and natural language processing (NLP), this book is an excellent resource for business professionals, leaders, policymakers, researchers, academicians, and more.
Machine Learning For Data Science Handbook
DOWNLOAD
Author : Lior Rokach
language : en
Publisher: Springer Nature
Release Date : 2023-08-17
Machine Learning For Data Science Handbook written by Lior Rokach and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-08-17 with Computers categories.
This book organizes key concepts, theories, standards, methodologies, trends, challenges and applications of data mining and knowledge discovery in databases. It first surveys, then provides comprehensive yet concise algorithmic descriptions of methods, including classic methods plus the extensions and novel methods developed recently. It also gives in-depth descriptions of data mining applications in various interdisciplinary industries.
Fundamentals Of Data Science
DOWNLOAD
Author : Mr.Desidi Narsimha Reddy
language : en
Publisher: Leilani Katie Publication
Release Date : 2024-09-05
Fundamentals Of Data Science written by Mr.Desidi Narsimha Reddy and has been published by Leilani Katie Publication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-05 with Computers categories.
Mr.Desidi Narsimha Reddy, Data Consultant (Data Governance, Data Analytics: Enterprise Performance Management, AI & ML), Soniks consulting LLC, 101 E Park Blvd Suite 600, Plano, TX 75074, United States. Lova Naga Babu Ramisetti, EPM Consultant, Department of Information Technology, MiniSoft Empowering Techonolgy, 10333 Harwin Dr. #375e, Houston, TX 77036, USA. Mr.Harikrishna Pathipati, EPM Manager, Department of Information Technology, ITG Technologies, 10998 S Wilcrest Dr, Houston, TX 77099, USA.
Advanced Ai And Data Science Applications
DOWNLOAD
Author : D. Sivabalaselvamani
language : en
Publisher: CRC Press
Release Date : 2025-09-25
Advanced Ai And Data Science Applications written by D. Sivabalaselvamani and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-09-25 with Computers categories.
Advanced AI and Data Science Applications explores how the latest developments in artificial intelligence (AI) and data science are transforming diverse domains. The book blends theory and practice to serve as a roadmap to help readers understand how these cutting-edge technologies are revolutionizing practices across various fields. By providing a mix of theoretical insights and practical implementations, the book offers a holistic understanding of advanced AI and data science applications. Highlights of the book include: Metaheuristic optimization techniques for solving complex AI model training challenges The impact of AI and data science on urban development Implementing AI for enhanced cybersecurity in industrial control systems A comparative study of traditional and AI-based methods for English speech recognition Temporal dependency modeling in real-time data streams using a deep learning model Predictive analytics for financial fraud detection and risk management Data science in manufacturing for cost reduction and efficiency AI-driven agricultural analytics Featuring such advanced modeling techniques as predictive modeling, simulation, and optimization algorithms, the book presents innovative solutions that emphasize benefits and practicality. With its emphasis on interdisciplinary applications, it showcases successful projects that underscore the synergy between AI and data science domains, empowering readers to harness the power of innovation for enhanced problem-solving and efficiency in interdisciplinary realms.
Big Data Science In Finance
DOWNLOAD
Author : Irene Aldridge
language : en
Publisher: John Wiley & Sons
Release Date : 2021-01-27
Big Data Science In Finance written by Irene Aldridge and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-01-27 with Computers categories.
Explains the mathematics, theory, and methods of Big Data as applied to finance and investing Data science has fundamentally changed Wall Street—applied mathematics and software code are increasingly driving finance and investment-decision tools. Big Data Science in Finance examines the mathematics, theory, and practical use of the revolutionary techniques that are transforming the industry. Designed for mathematically-advanced students and discerning financial practitioners alike, this energizing book presents new, cutting-edge content based on world-class research taught in the leading Financial Mathematics and Engineering programs in the world. Marco Avellaneda, a leader in quantitative finance, and quantitative methodology author Irene Aldridge help readers harness the power of Big Data. Comprehensive in scope, this book offers in-depth instruction on how to separate signal from noise, how to deal with missing data values, and how to utilize Big Data techniques in decision-making. Key topics include data clustering, data storage optimization, Big Data dynamics, Monte Carlo methods and their applications in Big Data analysis, and more. This valuable book: Provides a complete account of Big Data that includes proofs, step-by-step applications, and code samples Explains the difference between Principal Component Analysis (PCA) and Singular Value Decomposition (SVD) Covers vital topics in the field in a clear, straightforward manner Compares, contrasts, and discusses Big Data and Small Data Includes Cornell University-tested educational materials such as lesson plans, end-of-chapter questions, and downloadable lecture slides Big Data Science in Finance: Mathematics and Applications is an important, up-to-date resource for students in economics, econometrics, finance, applied mathematics, industrial engineering, and business courses, and for investment managers, quantitative traders, risk and portfolio managers, and other financial practitioners.
Financial Data Science With Sas
DOWNLOAD
Author : Babatunde O Odusami
language : en
Publisher: SAS Institute
Release Date : 2024-06-14
Financial Data Science With Sas written by Babatunde O Odusami and has been published by SAS Institute this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-06-14 with Computers categories.
Explore financial data science using SAS. Financial Data Science with SAS provides readers with a comprehensive explanation of the theoretical and practical implementation of the various types of analytical techniques and quantitative tools that are used in the financial services industry. This book shows readers how to implement data visualization, simulation, statistical predictive models, machine learning models, and financial optimizations using real-world examples in the SAS Analytics environment. Each chapter ends with practice exercises that include use case scenarios to allow readers to test their knowledge. Designed for university students and financial professionals interested in boosting their data science skills, Financial Data Science with SAS is an essential reference guide for understanding how data science is used in the financial services industry and for learning how to use SAS to solve complex business problems.
Machine Learning And Data Science Techniques For Effective Government Service Delivery
DOWNLOAD
Author : Ogunleye, Olalekan Samuel
language : en
Publisher: IGI Global
Release Date : 2024-03-27
Machine Learning And Data Science Techniques For Effective Government Service Delivery written by Ogunleye, Olalekan Samuel and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-03-27 with Political Science categories.
In our data-rich era, extracting meaningful insights from the vast amount of information has become a crucial challenge, especially in government service delivery where informed decisions are paramount. Traditional approaches struggle with the enormity of data, highlighting the need for a new approach that integrates data science and machine learning. The book, Machine Learning and Data Science Techniques for Effective Government Service Delivery, becomes a vital resource in this transformation, offering a deep understanding of these technologies and their applications. Within the complex landscape of modern governance, this book stands as a solution-oriented guide. Recognizing data's value in the 21st century, it navigates the world of data science and machine learning, enhancing the mechanics of government service. By addressing citizens' evolving needs, these advanced methods counter inefficiencies in traditional systems. Tailored for experts across technology, academia, and government, the book bridges theory and practicality. Covering foundational concepts and innovative applications, it explores the potential of data-driven decision-making for a more efficient and citizen-centric government future.
Machine Learning Optimization And Data Science
DOWNLOAD
Author : Giuseppe Nicosia
language : en
Publisher: Springer Nature
Release Date : 2023-03-08
Machine Learning Optimization And Data Science written by Giuseppe Nicosia and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-03-08 with Computers categories.
This two-volume set, LNCS 13810 and 13811, constitutes the refereed proceedings of the 8th International Conference on Machine Learning, Optimization, and Data Science, LOD 2022, together with the papers of the Second Symposium on Artificial Intelligence and Neuroscience, ACAIN 2022. The total of 84 full papers presented in this two-volume post-conference proceedings set was carefully reviewed and selected from 226 submissions. These research articles were written by leading scientists in the fields of machine learning, artificial intelligence, reinforcement learning, computational optimization, neuroscience, and data science presenting a substantial array of ideas, technologies, algorithms, methods, and applications.
Modern Artificial Intelligence And Data Science
DOWNLOAD
Author : Abdellah Idrissi
language : en
Publisher: Springer Nature
Release Date : 2023-08-25
Modern Artificial Intelligence And Data Science written by Abdellah Idrissi and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-08-25 with Computers categories.
This Book, through its various chapters presenting the Recent Advances in Modern Artificial Intelligence and Data Science as well as their Applications, aims to set up lasting and real applications necessary for both academics and professionals. Readers find here the fruit of many research ideas covering a wide range of application areas that can be explored for the advancement of their research or the development of their business. These ideas present new techniques and trends projected in various areas of daily life. Through its proposals of new ideas, this Book serves as a real guide both for experienced readers and for beginners in these specialized fields. It also covers several applications that explain how they can support some societal challenges such as education, health, agriculture, clean energy, business, environment, security and many more. This Book is therefore intended for Designers, Developers, Decision-Makers, Consultants, Engineers, and of course Master's/Doctoral Students, Researchers and Academics.