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Machine Learning And Pattern Recognition Methods In Chemistry From Multivariate And Data Driven Modeling
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Book Synopsis Machine Learning and Pattern Recognition Methods in Chemistry from Multivariate and Data Driven Modeling by : Jahan B. Ghasemi
Download or read book Machine Learning and Pattern Recognition Methods in Chemistry from Multivariate and Data Driven Modeling written by Jahan B. Ghasemi and published by Elsevier. This book was released on 2022-10-20 with total page 212 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine Learning and Pattern Recognition Methods in Chemistry from Multivariate and Data Driven Modeling outlines key knowledge in this area, combining critical introductory approaches with the latest advanced techniques. Beginning with an introduction of univariate and multivariate statistical analysis, the book then explores multivariate calibration and validation methods. Soft modeling in chemical data analysis, hyperspectral data analysis, and autoencoder applications in analytical chemistry are then discussed, providing useful examples of the techniques in chemistry applications. Drawing on the knowledge of a global team of researchers, this book will be a helpful guide for chemists interested in developing their skills in multivariate data and error analysis. Provides an introductory overview of statistical methods for the analysis and interpretation of chemical data Discusses the use of machine learning for recognizing patterns in multidimensional chemical data Identifies common sources of multivariate errors
Book Synopsis Machine Learning and Interpretation in Neuroimaging by : Georg Langs
Download or read book Machine Learning and Interpretation in Neuroimaging written by Georg Langs and published by Springer. This book was released on 2012-11-11 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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, and engineering. Thus, methodological and technological advances that enable us to obtain measurements, examine relationships across observations, and link these data to neuroscientific hypotheses happen in a highly interdisciplinary environment. The dynamic field of machine learning with its modern approach to data mining provides many relevant approaches for neuroscience and enables the exploration of open questions. This state-of-the-art survey offers a collection of papers from the Workshop on Machine Learning and Interpretation in Neuroimaging, MLINI 2011, held at the 25th Annual Conference on Neural Information Processing, NIPS 2011, in the Sierra Nevada, Spain, in December 2011. Additionally, invited speakers agreed to contribute reviews on various aspects of the field, adding breadth and perspective to the volume. The 32 revised papers were carefully selected from 48 submissions. At the interface between machine learning and neuroimaging the papers aim at shedding some light on the state of the art in this interdisciplinary field. They are organized in topical sections on coding and decoding, neuroscience, dynamcis, connectivity, and probabilistic models and machine learning.
Book Synopsis Machine Learning in Chemistry by : Edward O. Pyzer-Knapp
Download or read book Machine Learning in Chemistry written by Edward O. Pyzer-Knapp and published by . This book was released on 2020-10-22 with total page 140 pages. Available in PDF, EPUB and Kindle. Book excerpt: Atomic-scale representation and statistical learning of tensorial properties -- Prediction of Mohs hardness with machine learning methods using compositional features -- High-dimensional neural network potentials for atomistic simulations -- Data-driven learning systems for chemical reaction prediction: an analysis of recent approaches -- Using machine learning to inform decisions in drug discovery : an industry perspective -- Cognitive materials discovery and onset of the 5th discovery paradigm.
Book Synopsis Machine Learning in Chemistry by : Jon Paul Janet
Download or read book Machine Learning in Chemistry written by Jon Paul Janet and published by American Chemical Society. This book was released on 2020-05-28 with total page 189 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recent advances in machine learning or artificial intelligence for vision and natural language processing that have enabled the development of new technologies such as personal assistants or self-driving cars have brought machine learning and artificial intelligence to the forefront of popular culture. The accumulation of these algorithmic advances along with the increasing availability of large data sets and readily available high performance computing has played an important role in bringing machine learning applications to such a wide range of disciplines. Given the emphasis in the chemical sciences on the relationship between structure and function, whether in biochemistry or in materials chemistry, adoption of machine learning by chemistsderivations where they are important
Book Synopsis Chemometrics for Pattern Recognition by : Richard G. Brereton
Download or read book Chemometrics for Pattern Recognition written by Richard G. Brereton and published by John Wiley & Sons. This book was released on 2009-06-29 with total page 522 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the past decade, pattern recognition has been one of the fastest growth points in chemometrics. This has been catalysed by the increase in capabilities of automated instruments such as LCMS, GCMS, and NMR, to name a few, to obtain large quantities of data, and, in parallel, the significant growth in applications especially in biomedical analytical chemical measurements of extracts from humans and animals, together with the increased capabilities of desktop computing. The interpretation of such multivariate datasets has required the application and development of new chemometric techniques such as pattern recognition, the focus of this work. Included within the text are: ‘Real world’ pattern recognition case studies from a wide variety of sources including biology, medicine, materials, pharmaceuticals, food, forensics and environmental science; Discussions of methods, many of which are also common in biology, biological analytical chemistry and machine learning; Common tools such as Partial Least Squares and Principal Components Analysis, as well as those that are rarely used in chemometrics such as Self Organising Maps and Support Vector Machines; Representation in full colour; Validation of models and hypothesis testing, and the underlying motivation of the methods, including how to avoid some common pitfalls. Relevant to active chemometricians and analytical scientists in industry, academia and government establishments as well as those involved in applying statistics and computational pattern recognition.
Book Synopsis Machine Learning and Hybrid Modelling for Reaction Engineering by : Dongda Zhang
Download or read book Machine Learning and Hybrid Modelling for Reaction Engineering written by Dongda Zhang and published by Royal Society of Chemistry. This book was released on 2023-12-20 with total page 441 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Data Science and Machine Learning by : Dirk P. Kroese
Download or read book Data Science and Machine Learning written by Dirk P. Kroese and published by CRC Press. This book was released on 2019-11-20 with total page 538 pages. Available in PDF, EPUB and Kindle. Book excerpt: Focuses on mathematical understanding Presentation is self-contained, accessible, and comprehensive Full color throughout Extensive list of exercises and worked-out examples Many concrete algorithms with actual code
Book Synopsis Unsupervised Process Monitoring and Fault Diagnosis with Machine Learning Methods by : Chris Aldrich
Download or read book Unsupervised Process Monitoring and Fault Diagnosis with Machine Learning Methods written by Chris Aldrich and published by Springer Science & Business Media. This book was released on 2013-06-15 with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt: This unique text/reference describes in detail the latest advances in unsupervised process monitoring and fault diagnosis with machine learning methods. Abundant case studies throughout the text demonstrate the efficacy of each method in real-world settings. The broad coverage examines such cutting-edge topics as the use of information theory to enhance unsupervised learning in tree-based methods, the extension of kernel methods to multiple kernel learning for feature extraction from data, and the incremental training of multilayer perceptrons to construct deep architectures for enhanced data projections. Topics and features: discusses machine learning frameworks based on artificial neural networks, statistical learning theory and kernel-based methods, and tree-based methods; examines the application of machine learning to steady state and dynamic operations, with a focus on unsupervised learning; describes the use of spectral methods in process fault diagnosis.
Book Synopsis Machine Learning and Data-Driven Research in Chemistry by : Hachmann
Download or read book Machine Learning and Data-Driven Research in Chemistry written by Hachmann and published by Wiley-Blackwell. This book was released on 2017-12-08 with total page 524 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Machine Learning-Based Modelling in Atomic Layer Deposition Processes by : Oluwatobi Adeleke
Download or read book Machine Learning-Based Modelling in Atomic Layer Deposition Processes written by Oluwatobi Adeleke and published by CRC Press. This book was released on 2023-12-15 with total page 353 pages. Available in PDF, EPUB and Kindle. Book excerpt: While thin film technology has benefited greatly from artificial intelligence (AI) and machine learning (ML) techniques, there is still much to be learned from a full-scale exploration of these technologies in atomic layer deposition (ALD). This book provides in-depth information regarding the application of ML-based modeling techniques in thin film technology as a standalone approach and integrated with the classical simulation and modeling methods. It is the first of its kind to present detailed information regarding approaches in ML-based modeling, optimization, and prediction of the behaviors and characteristics of ALD for improved process quality control and discovery of new materials. As such, this book fills significant knowledge gaps in the existing resources as it provides extensive information on ML and its applications in film thin technology. Offers an in-depth overview of the fundamentals of thin film technology, state-of-the-art computational simulation approaches in ALD, ML techniques, algorithms, applications, and challenges. Establishes the need for and significance of ML applications in ALD while introducing integration approaches for ML techniques with computation simulation approaches. Explores the application of key techniques in ML, such as predictive analysis, classification techniques, feature engineering, image processing capability, and microstructural analysis of deep learning algorithms and generative model benefits in ALD. Helps readers gain a holistic understanding of the exciting applications of ML-based solutions to ALD problems and apply them to real-world issues. Aimed at materials scientists and engineers, this book fills significant knowledge gaps in existing resources as it provides extensive information on ML and its applications in film thin technology. It also opens space for future intensive research and intriguing opportunities for ML-enhanced ALD processes, which scale from academic to industrial applications. . .
Book Synopsis Chemoinformatics and Advanced Machine Learning Perspectives: Complex Computational Methods and Collaborative Techniques by : Lodhi, Huma
Download or read book Chemoinformatics and Advanced Machine Learning Perspectives: Complex Computational Methods and Collaborative Techniques written by Lodhi, Huma and published by IGI Global. This book was released on 2010-07-31 with total page 418 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book is a timely compendium of key elements that are crucial for the study of machine learning in chemoinformatics, giving an overview of current research in machine learning and their applications to chemoinformatics tasks"--Provided by publisher.
Download or read book Chemosensors written by Binghe Wang and published by John Wiley & Sons. This book was released on 2011-08-24 with total page 830 pages. Available in PDF, EPUB and Kindle. Book excerpt: A thorough, accessible, and general overview of chemosensors Providing a comprehensive overview of chemosensors organic molecules designed to bind and sense small molecules or metal ions and their applications, Chemosensors: Principles, Strategies, and Applications is an accessible one-stop resource for analysts, clinicians, and graduate students studying advanced chemistry and chemosensing. Chemosensors function on a molecular level, generating a signal upon binding. The book reviews their synthesis, design, and applications for detecting biological and organic molecules as well as metal ions. The text highlights applications in drug discovery and catalyses that have not been well covered elsewhere. Covering such topics as molecular recognition, detection methods, design strategies, and important biological issues, the book is broken into four sections that examine intermolecular interactions, strategies in sensor design, detection methods, and case studies in metal, saccharide, and amino acid sensing. An indispensable source of information for chemical and biomedical experts using sensors, Chemosensors includes case studies to make the material both accessible and understandable to chemists of all backgrounds.
Book Synopsis The Practice of Medicinal Chemistry by : Camille Georges Wermuth
Download or read book The Practice of Medicinal Chemistry written by Camille Georges Wermuth and published by Academic Press. This book was released on 2011-05-02 with total page 982 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Practice of Medicinal Chemistry fills a gap in the list of available medicinal chemistry literature. It is a single-volume source on the practical aspects of medicinal chemistry. Considered ""the Bible"" by medicinal chemists, the book emphasizes the methods that chemists use to conduct their research and design new drug entities. It serves as a practical handbook about the drug discovery process, from conception of the molecules to drug production. The first part of the book covers the background of the subject matter, which includes the definition and history of medicinal chemistry, the measurement of biological activities, and the main phases of drug activity. The second part of the book presents the road to discovering a new lead compound and creating a working hypothesis. The main parts of the book discuss the optimization of the lead compound in terms of potency, selectivity, and safety. The Practice of Medicinal Chemistry can be considered a ""first-read"" or ""bedside book"" for readers who are embarking on a career in medicinal chemistry. NEW TO THIS EDITION: * Focus on chemoinformatics and drug discovery * Enhanced pedagogical features* New chapters including: - Drug absorption and transport - Multi-target drugs* Updates on hot new areas: NEW! Drug discovery and the latest techniques NEW! How potential drugs can move through the drug discovery/ development phases more quickly NEW! Chemoinformatics
Download or read book Air Force Research Resumés written by and published by . This book was released on with total page 854 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Statistical Modelling of Molecular Descriptors in QSAR/QSPR by : Matthias Dehmer
Download or read book Statistical Modelling of Molecular Descriptors in QSAR/QSPR written by Matthias Dehmer and published by John Wiley & Sons. This book was released on 2012-09-13 with total page 437 pages. Available in PDF, EPUB and Kindle. Book excerpt: This handbook and ready reference presents a combination of statistical, information-theoretic, and data analysis methods to meet the challenge of designing empirical models involving molecular descriptors within bioinformatics. The topics range from investigating information processing in chemical and biological networks to studying statistical and information-theoretic techniques for analyzing chemical structures to employing data analysis and machine learning techniques for QSAR/QSPR. The high-profile international author and editor team ensures excellent coverage of the topic, making this a must-have for everyone working in chemoinformatics and structure-oriented drug design.
Book Synopsis Women in Analytical Chemistry by : Nicole J. Jaffrezic-Renault
Download or read book Women in Analytical Chemistry written by Nicole J. Jaffrezic-Renault and published by Frontiers Media SA. This book was released on 2022-09-22 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Machine Learning for Materials Discovery by : N. M. Anoop Krishnan
Download or read book Machine Learning for Materials Discovery written by N. M. Anoop Krishnan and published by Springer. This book was released on 2024-03-19 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Focusing on the fundamentals of machine learning, this book covers broad areas of data-driven modeling, ranging from simple regression to advanced machine learning and optimization methods for applications in materials modeling and discovery. The book explains complex mathematical concepts in a lucid manner to ensure that readers from different materials domains are able to use these techniques successfully. A unique feature of this book is its hands-on aspect—each method presented herein is accompanied by a code that implements the method in open-source platforms such as Python. This book is thus aimed at graduate students, researchers, and engineers to enable the use of data-driven methods for understanding and accelerating the discovery of novel materials.
