Описание: With the field of computational statistics growing rapidly, there is a need for capturing the advances and assessing their impact. Advances in simulation and graphical analysis also add to the pace of the statistical analytics field. Computational statistics play a key role in financial applications, particularly risk management and derivative pricing, biological applications including bioinformatics and computational biology, and computer network security applications that touch the lives of people. With high impacting areas such as these, it becomes important to dig deeper into the subject and explore the key areas and their progress in the recent past.
Methodologies and Applications of Computational Statistics for Machine Intelligence serves as a guide to the applications of new advances in computational statistics. This text holds an accumulation of the thoughts of multiple experts together, keeping the focus on core computational statistics that apply to all domains. Covering topics including artificial intelligence, deep learning, and trend analysis, this book is an ideal resource for statisticians, computer scientists, mathematicians, lecturers, tutors, researchers, academic and corporate libraries, practitioners, professionals, students, and academicians.
Описание: With the field of computational statistics growing rapidly, there is a need for capturing the advances and assessing their impact. Advances in simulation and graphical analysis also add to the pace of the statistical analytics field. Computational statistics play a key role in financial applications, particularly risk management and derivative pricing, biological applications including bioinformatics and computational biology, and computer network security applications that touch the lives of people. With high impacting areas such as these, it becomes important to dig deeper into the subject and explore the key areas and their progress in the recent past.
Methodologies and Applications of Computational Statistics for Machine Intelligence serves as a guide to the applications of new advances in computational statistics. This text holds an accumulation of the thoughts of multiple experts together, keeping the focus on core computational statistics that apply to all domains. Covering topics including artificial intelligence, deep learning, and trend analysis, this book is an ideal resource for statisticians, computer scientists, mathematicians, lecturers, tutors, researchers, academic and corporate libraries, practitioners, professionals, students, and academicians.
Описание: Highlights the marriage between business intelligence and knowledge management through the use of agile methodologies. Through its fifteen chapters, this offers perspectives on the integration between process modeling, agile methodologies, business intelligence, knowledge management, and strategic management.
Автор: Aboul Ella Hassanien, Ashraf Darwish, Chiranji Lal Chowdhary Название: Handbook of Research on Deep Learning Innovations and Trends ISBN: 1522578625 ISBN-13(EAN): 9781522578628 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 43105.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Leading technology firms and research institutions are continuously exploring new techniques in artificial intelligence and machine learning. As such, deep learning has now been recognized in various real-world applications such as computer vision, image processing, biometrics, pattern recognition, and medical imaging. The deep learning approach has opened new opportunities that can make such real-life applications and tasks easier and more efficient. The Handbook of Research on Deep Learning Innovations and Trends is an essential scholarly resource that presents current trends and the latest research on deep learning and explores the concepts, algorithms, and techniques of data mining and analysis. Highlighting topics such as computer vision, encryption systems, and biometrics, this book is ideal for researchers, practitioners, industry professionals, students, and academicians.
Описание: Based on the tutorials presented at the INNS Big Data and Deep Learning Conference, INNSBDDL2019, held on April 16-18, 2019, in Sestri Levante, Italy, the respective chapters cover advanced neural networks, deep architectures, and supervised and reinforcement machine learning models.
Автор: Singh Pradeep Kumar, Panigrahi Bijaya Ketan, Suryadevara Nagender Kumar Название: Proceedings of Icetit 2019: Emerging Trends in Information Technology ISBN: 3030305791 ISBN-13(EAN): 9783030305796 Издательство: Springer Рейтинг: Цена: 36589.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Discover the fantastic history of the saboteurs during World War II in the French resistance. Trained by the British secret service, they destroyed hundreds of buildings, bridges, and industries. Leading up to D-Day they blocked the German forces by destroying transport links and sabotaged German military production in France.
Описание: Face Recognition using Raspberry PI.- Features Extraction for Network Intrusion Detection using Genetic Algorithm(GA).- Chemical Sensing through Cogno-Monitoring System for Air Quality Evaluation.- 3 DOF Autonomous Control Analysis of an Quadcopter Using Artificial Neural Network.- Cognitive Demand Forecasting with Novel Features using Word2Vec and Session of the Day.- A Curvelet Transformer Based Computationally Efficient Speech Enhancement for Kalman Filter.- Dexterous Trashbot.- Automated Question Generation and Answer Verification using Visual Data.- Comprehensive Survey on Deep Learning Approaches in Predictive Business Process Monitoring.- Machine Learning Based Risk-Adaptive Access Control System to Identify Genuineness of the Requester.- An Approach to End to End Anonymity.- PHT and KELM Based Face Recognition.- Link Failure Detection in MANET: A Survey.- Review of Low Power Techniques for Neural Recording Applications.- Machine Learning Techniques for Thyroid Disease Diagnosis: A Systematic Review.- Heuristic Approach to Evaluate the Performance of Optimization Algorithms in VLSI Floor Planning for ASIC design.- Enhancement in Teaching Quality Methodology by Predicting Attendance using Machine Learning Technique.- Improvement in Extended Object tracking with the Vision-Based Algorithm.
Автор: Jain Shruti, Paul Sudip Название: Recent Trends in Image and Signal Processing in Computer Vision ISBN: 9811527393 ISBN-13(EAN): 9789811527395 Издательство: Springer Рейтинг: Цена: 12196.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book highlights recent advances and emerging technologies that utilize computational intelligence in signal processing, computing, imaging science, artificial intelligence, and their applications. artificial neural networks, evolutionary algorithms, fuzzy systems, and automatic medical identification systems.
We often hear that AI is revolutionising the financial sector, like no other technology has done before. This book looks beyond these clich s and explores all aspects of this transformation at a deep level. It spells out a vision for the future and answers many questions that are routinely ignored.
What do we mean by Artificial Intelligence in finance? How do we move past the myths and misconceptions to reveal the key driving forces?
What are the industry trends that align with this transformation? Is it the explosion of digital touchpoints in retail, the reduced risk taking by investment banks, or the ascent of passive funds in asset management?
How do we develop concrete use cases from idea generation to production? How do we engineer systems to make accurate predictions, offer recommendations to clients, or analyse unstructured news data?
How do we build a successful data-driven organisation? What are the key pitfalls to avoid? Is it about culture, data governance, or management vision?
What are the risks specific to developing AI technologies? Can we humans understand and explain what the machines produce for us? Can we trust their predictions or actions?
What is the role of alternative data in all this? How can we put it to use for augmented insight?
What are the problems that AI is well equipped to solve? Is it all about neural networks and deep learning, as we regularly hear in the popular press? How do we understand human language, a task so important to the financial analyst?
The book is packed with concrete examples from the various disciplines of finance. Interested readers will also develop a deep understanding of AI algorithms - presented in plain English - and learn how to solve the most challenging problems. But first and foremost, it is a practical book that equips finance executives with everything they need to understand this transformation and to become agents of change themselves.
Описание: This book constitutes revised selected papers from the Second International Workshop on Future and Emerging Trends in Language Technology, FETLT 2016, which took place in Seville, Spain, in November 2016. The 10 full papers and 5 position papers presented in this volume were carefully reviewed and selected from 18 submissions.
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