Computational and Data Driven Chemistry Using Artificial Intelligence

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  • Author : Takashiro Akitsu
  • Publisher : Elsevier
  • Pages : 310 pages
  • ISBN : 0128232722
  • Rating : /5 from reviews
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Download or Read online Computational and Data Driven Chemistry Using Artificial Intelligence full in PDF, ePub and kindle. this book written by Takashiro Akitsu and published by Elsevier which was released on 15 October 2021 with total page 310 pages. We cannot guarantee that Computational and Data Driven Chemistry Using Artificial Intelligence book is available in the library, click Get Book button and read full online book in your kindle, tablet, IPAD, PC or mobile whenever and wherever You Like. Computational and Data-Driven Chemistry Using Artificial Intelligence: Volume 1: Fundamentals, Methods and Applications highlights fundamental knowledge and current developments in the field, giving readers insight into how these tools can be harnessed to enhance their own work. Offering the ability to process large or complex data-sets, compare molecular characteristics and behaviors, and help researchers design or identify new structures, Artificial Intelligence (AI) holds huge potential to revolutionize the future of chemistry. Volume 1 explores the fundamental knowledge and current methods being used to apply AI across a whole host of chemistry applications. Drawing on the knowledge of its expert team of global contributors, the book offers fascinating insight into this rapidly developing field and serves as a great resource for all those interested in exploring the opportunities afforded by the intersection of chemistry and AI in their own work. Part 1 provides foundational information on AI in chemistry, with an introduction to the field and guidance on database usage and statistical analysis to help support newcomers to the field. Part 2 then goes on to discuss approaches currently used to address problems in broad areas such as computational and theoretical chemistry; materials, synthetic and medicinal chemistry; crystallography, analytical chemistry, and spectroscopy. Finally, potential future trends in the field are discussed. Provides an accessible introduction to the current state and future possibilities for AI in chemistry Explores how computational chemistry methods and approaches can both enhance and be enhanced by AI Highlights the interdisciplinary and broad applicability of AI tools across a wide range of chemistry fields

Computational and Data Driven Chemistry Using Artificial Intelligence

Computational and Data Driven Chemistry Using Artificial Intelligence
  • Author : Takashiro Akitsu
  • Publisher : Elsevier
  • Release : 15 October 2021
GET THIS BOOK Computational and Data Driven Chemistry Using Artificial Intelligence

Computational and Data-Driven Chemistry Using Artificial Intelligence: Volume 1: Fundamentals, Methods and Applications highlights fundamental knowledge and current developments in the field, giving readers insight into how these tools can be harnessed to enhance their own work. Offering the ability to process large or complex data-sets, compare molecular characteristics and behaviors, and help researchers design or identify new structures, Artificial Intelligence (AI) holds huge potential to revolutionize the future of chemistry. Volume 1 explores the fundamental knowledge and current methods being used

Machine Learning in Chemistry

Machine Learning in Chemistry
  • Author : Edward O. Pyzer-Knapp,Teodoro Laino
  • Publisher : Unknown
  • Release : 22 October 2020
GET THIS BOOK Machine Learning in Chemistry

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.

Applications of Computational Intelligence in Data Driven Trading

Applications of Computational Intelligence in Data Driven Trading
  • Author : Cris Doloc
  • Publisher : John Wiley & Sons
  • Release : 29 October 2019
GET THIS BOOK Applications of Computational Intelligence in Data Driven Trading

“Life on earth is filled with many mysteries, but perhaps the most challenging of these is the nature of Intelligence.” – Prof. Terrence J. Sejnowski, Computational Neurobiologist The main objective of this book is to create awareness about both the promises and the formidable challenges that the era of Data-Driven Decision-Making and Machine Learning are confronted with, and especially about how these new developments may influence the future of the financial industry. The subject of Financial Machine Learning has attracted a

Computational Intelligence and Feature Selection

Computational Intelligence and Feature Selection
  • Author : Richard Jensen,Qiang Shen
  • Publisher : Wiley-IEEE Press
  • Release : 29 September 2008
GET THIS BOOK Computational Intelligence and Feature Selection

The rough and fuzzy set approaches presented here open up many new frontiers for continued research and development Computational Intelligence and Feature Selection provides readers with the background and fundamental ideas behind Feature Selection (FS), with an emphasis on techniques based on rough and fuzzy sets. For readers who are less familiar with the subject, the book begins with an introduction to fuzzy set theory and fuzzy-rough set theory. Building on this foundation, the book provides: A critical review of