A groundbreaking, authoritative introduction to how machine learning can be applied to asset pricingInvestors in financial markets are faced with an abundance of potentially valuerelevant...
The idea for this book came from the time the authors spent at the Statistics and Applied Mathematical Sciences Institute (SAMSI) in Research Triangle Park...
Increasingly, crimes and fraud are digital in nature, occurring at breakneck speed and encompassing large volumes of data. To combat this unlawful activity, knowledge about...
Machine Learning:Discriminative and Generative covers the main contemporary themes and tools in machine learning ranging from Bayesian probabilistic models to discriminative supportvector machines. However, unlike...
Book Description In the early 1990s, the establishment of the Internet brought forth a revolutionary viewpoint of information storage, distribution, and the World Wide Web...
Machine learning allows computers to learn and discern patterns without actually being programmed. When Statistical techniques and machine learning are combined together they are a...
Machine Learning: A ConstraintBased Approach provides readers with a refreshing look at the basic models and algorithms of machine learning, with an emphasis on current...
Written by leading researchers in the field, Machine Learning for Tomographic Imaging presents a unified overview of deeplearningbased tomographic imaging. Key concepts, including classic reconstruction...
From the Foreword:"While largescale machine learning and data mining have greatly impacted a range of commercial applications, their use in the field of Earth sciences...
Put the power of AWS Cloud machine learning services to work in your business and commercial applications!Machine Learning in the AWS Cloud introduces readers to...
This book presents the features and advantages offered by complex networks in the machine learning domain. In the first part, an overview on complex networks...
This textbook introduces linear algebra and optimization in the context of machine learning. Examples and exercises are provided throughout the book. A solution manual for...
Markov Decision Processes (MDPs) are widely popular in Artificial Intelligence for modeling sequential decisionmaking scenarios with probabilistic dynamics. They are the framework of choice when...
This book provides the mathematical fundamentals of linear algebra to practicers in computer vision, machine learning, robotics, applied mathematics, and electrical engineering. By only assuming...
Master machine learning techniques with R to deliver insights in complex projectsKey Features Understand and apply machine learning methods using an extensive set of R...
In corpus linguistics, partofspeech tagging (POS tagging or POST), also called grammatical tagging or wordcategory disambiguation, is the process of marking up the words in...
A collection of shockingly prescient stories covering topics from aliens to AI, including some that have never before been seen, from the New York Times...
A collection of shockingly prescient stories covering topics from aliens to AI, including some that have never before been seen, from the New York Times...
Brain imaging brings together the technology, methodology, research questions and approaches of a wide range of scientific fields including physics, statistics, computer science, neuroscience, biology,...
This book describes in detail the fundamental mathematics and algorithms of machine learning (an example of artificial intelligence) and signal processing, two of the most...
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Your nononsense guide to making sense of machine learningMachine learning can be a mindboggling concept for the masses, but those who are in the trenches...
With a machine learning approach and less focus on linguistic details, this gentle introduction to natural language processing develops fundamental mathematical and deep learning models...
Offering a fundamental basis in kernelbased learning theory, this book covers both statistical and algebraic principles. It provides over 30 major theorems for kernelbased supervised...
Graphics in this book are printed in black and white.This book includes :Excel VBA : A StepByStep Tutorial For Beginners To Learn Excel VBA Programming...
Machine Learning: An Artificial Intelligence Approach contains tutorial overviews and research papers representative of trends in the area of machine learning as viewed from an...
Diagnosisrelated groups (DRGs) are used in hospitals for the reimbursement of inpatient services. The assignment of a patient to a DRG can be distinguished into...
Product Description This book constitutes the refereed proceedings of the 7th International Conference on Machine Learning and Data Mining in Pattern Recognition, MLDM 2011, held...
This book constitutes the refereed proceedings of the 13th International Conference on Machine Learning and Cybernetics, Lanzhou, China, in July 2014. The 45 revised full...
Machine learning is concerned with the analysis of large data and multiple variables. It is also often more sensitive than traditional statistical methods to analyze...
Master expert techniques for building automated and highly scalable endtoend machine learning models and pipelines in Azure using TensorFlow, Spark, and KubernetesKey Features Make sense...
Product Description Data fusion problems arise frequently in many different fields. This book provides a specific introduction to data fusion problems using support vector machines....
This book constitutes the thoroughly refereed postproceedings of the 4th International Workshop on Machine Learning for Multimodal Interaction, MLMI 2007, held in Brno, Czech Republic,...
This twovolume set LNAI 10934 and LNAI 10935 constitutes the refereed proceedings of the 14th International Conference on Machine Learning and Data Mining in Pattern...
This book constitutes the refereed postconference proceedings of the International Conference on Machine Learning and Intelligent Communications, MLICOM 2016, held in Shanghai, China in August...
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